Understanding Coronal Heating through Time-Series Analysis and Nanoflare Modeling

NASA Astrophysics Data System (ADS)

Romich, Kristine; Viall, Nicholeen

2018-01-01

Periodic intensity fluctuations in coronal loops, a signature of temperature evolution, have been observed using the Atmospheric Imaging Assembly (AIA) aboard NASA’s Solar Dynamics Observatory (SDO) spacecraft. We examine the proposal that nanoflares, or impulsive bursts of energy release in the solar atmosphere, are responsible for the intensity fluctuations as well as the megakelvin-scale temperatures observed in the corona. Drawing on the work of Cargill (2014) and Bradshaw & Viall (2016), we develop a computer model of the energy released by a sequence of nanoflare events in a single magnetic flux tube. We then use EBTEL (Enthalpy-Based Thermal Evolution of Loops), a hydrodynamic model of plasma response to energy input, to simulate intensity as a function of time across the coronal AIA channels. We test the EBTEL output for periodicities using a spectral code based on Mann and Lees’ (1996) multitaper method and present preliminary results here. Our ultimate goal is to establish whether quasi-continuous or impulsive energy bursts better approximate the original SDO data.

The Sun-Earth connect 3: lessons from the periodicities of deep time influencing sea-level change and marine extinctions in the geological record.

PubMed

Baker, Robert Gv; Flood, Peter G

2015-01-01

A number of papers since Rampino and Stothers published in Science 1984 have reported common periodicities in a wide range of climate, geomagnetic, tectonic and biological proxies, including marine extinctions. Single taper and multitaper spectral analysis of marine fluctuations between the Late Cretaceous and the Miocene replicates a number of the published harmonics. Whereas these common periodicities have been argued to have a galactic origin, this paper presents an alternative fractal model based on large scale fluctuations of the magnetic field of the Sun. The fluctuations follow a self-similar matrix of periodicities and the solutions of the differential equation allow for models to be constructed predicting extreme events for solar emissions. A comparison to major Phanerozoic extinction, climate and geomagnetic events, captured in the geological record, show a striking loop symmetry summarised in major 66 Ma irradiance and electromagnetic pulses from the Sun.

Multi-tap complex-coefficient incoherent microwave photonic filters based on optical single-sideband modulation and narrow band optical filtering.

PubMed

Sagues, Mikel; García Olcina, Raimundo; Loayssa, Alayn; Sales, Salvador; Capmany, José

2008-01-07

We propose a novel scheme to implement tunable multi-tap complex coefficient filters based on optical single sideband modulation and narrow band optical filtering. A four tap filter is experimentally demonstrated to highlight the enhanced tuning performance provided by complex coefficients. Optical processing is performed by the use of a cascade of four phase-shifted fiber Bragg gratings specifically fabricated for this purpose.

Statistical description of tectonic motions

NASA Technical Reports Server (NTRS)

Agnew, Duncan Carr

1993-01-01

This report summarizes investigations regarding tectonic motions. The topics discussed include statistics of crustal deformation, Earth rotation studies, using multitaper spectrum analysis techniques applied to both space-geodetic data and conventional astrometric estimates of the Earth's polar motion, and the development, design, and installation of high-stability geodetic monuments for use with the global positioning system.

Oscillatory modes of extended Nile River records (A.D. 622-1922)

NASA Astrophysics Data System (ADS)

Kondrashov, D.; Feliks, Y.; Ghil, M.

2005-05-01

The historical records of the low- and high-water levels of the Nile River are among the longest climatic records that have near-annual resolution. There are few gaps in the first part of the records (A.D. 622-1470) and larger gaps later (A.D. 1471-1922). We apply advanced spectral methods, Singular-Spectrum Analysis (SSA) and the Multi-Taper Method (MTM), to fill the gaps and to locate interannual and interdecadal periodicities. The gap filling uses a novel, iterative version of SSA. Our analysis reveals several statistically significant features of the records: a nonlinear, data-adaptive trend that includes a 256-year cycle, a quasi-quadriennial (4.2-year) and a quasi-biennial (2.2-year) mode, as well as additional periodicities of 64, 19, 12, and, most strikingly, 7 years. The quasi-quadriennial and quasi-biennial modes support the long-established connection between the Nile River discharge and the El-Niño/Southern Oscillation (ENSO) phenomenon in the Indo-Pacific Ocean. The longest periods might be of astronomical origin. The 7-year periodicity, possibly related to the biblical cycle of lean and fat years, seems to be due to North Atlantic influences.

The identification of solar wind waves at discrete frequencies and the role of the spectral analysis techniques

NASA Astrophysics Data System (ADS)

Di Matteo, S.; Villante, U.

2017-05-01

The occurrence of waves at discrete frequencies in the solar wind (SW) parameters has been reported in the scientific literature with some controversial results, mostly concerning the existence (and stability) of favored sets of frequencies. On the other hand, the experimental results might be influenced by the analytical methods adopted for the spectral analysis. We focused attention on the fluctuations of the SW dynamic pressure (PSW) occurring in the leading edges of streams following interplanetary shocks and compared the results of the Welch method (WM) with those of the multitaper method (MTM). The results of a simulation analysis demonstrate that the identification of the wave occurrence and the frequency estimate might be strongly influenced by the signal characteristics and analytical methods, especially in the presence of multicomponent signals. In SW streams, PSW oscillations are routinely detected in the entire range f ≈ 1.2-5.0 mHz; nevertheless, the WM/MTM agreement in the identification and frequency estimate occurs in ≈50% of events and different sets of favored frequencies would be proposed for the same set of events by the WM and MTM analysis. The histogram of the frequency distribution of the events identified by both methods suggests more relevant percentages between f ≈ 1.7-1.9, f ≈ 2.7-3.4, and f ≈ 3.9-4.4 (with a most relevant peak at f ≈ 4.2 mHz). Extremely severe thresholds select a small number (14) of remarkable events, with a one-to-one correspondence between WM and MTM: interestingly, these events reveal a tendency for a favored occurrence in bins centered at f ≈ 2.9 and at f ≈ 4.2 mHz.

Understanding changes over time in workers' compensation claim rates using time series analytical techniques.

PubMed

Moore, Ian C; Tompa, Emile

2011-11-01

The objective of this study is to better understand the inter-temporal variation in workers' compensation claim rates using time series analytical techniques not commonly used in the occupational health and safety literature. We focus specifically on the role of unemployment rates in explaining claim rate variations. The major components of workers' compensation claim rates are decomposed using data from a Canadian workers' compensation authority for the period 1991-2007. Several techniques are used to undertake the decomposition and assess key factors driving rates: (i) the multitaper spectral estimator, (ii) the harmonic F test, (iii) the Kalman smoother and (iv) ordinary least squares. The largest component of the periodic behaviour in workers' compensation claim rates is seasonal variation. Business cycle fluctuations in workers' compensation claim rates move inversely to unemployment rates. The analysis suggests that workers' compensation claim rates between 1991 and 2008 were driven by (in order of magnitude) a strong negative long term growth trend, periodic seasonal trends and business cycle fluctuations proxied by the Ontario unemployment rate.

Towards a High-resolution Time Scale for the Early Devonian

NASA Astrophysics Data System (ADS)

Dekkers, M. J.; da Silva, A. C.

2017-12-01

High-resolution time scales are crucial to understand Earth's history in detail. The construction of a robust geological time scale, however, inevitably becomes increasingly harder further back in time. Uncertainties associated with anchor radiometric ages increase in size, not speaking of the mere presence of suitable datable strata. However, durations of stages can be tightly constrained by making use of cyclic expressions in sediments, an approach that revolutionized the Cenozoic time scale. When precisely determined durations are stitched together, ultimately, a very precise time scale is the result. For the Mesozoic and Paleozoic an astronomical solution as a tuning target is not available but the dominant periods of eccentricity, obliquity and precession are reasonably well constrained for the entire Phanerozoic which enables their detection by means of spectral analysis. Eccentricity is time-invariant and is used as the prime building block. Here we focus on the Early Devonian, on its lowermost three stages: the Lochkovian, Pragian and Emsian. The uncertainties on the Devonian stage boundaries are currently in the order of several millions of years. The preservation of climatic cycles in diagenetically or even anchimetamorphically affected successions, however, is essential. The fit of spectral peak ratios with those calculated for orbital cycles, is classically used as a strong argument for a preserved climatic signal. Here we use primarily the low field magnetic susceptibility (MS) as proxy parameter, supported by gamma-ray spectrometry to test for consistency. Continuous Wavelet Transform, Evolutive Harmonic Analysis, Multitaper Method, and Average Spectral Misfit are used to reach an optimal astronomical interpretation. We report on classic Early Devonian sections from the Czech Republic: the Pozar-CS (Lochkovian and Pragian), Pod Barrandovem (Pragian and Lower Emsian), and Zlichov (Middle-Upper Emsian). Also a Middle-Upper Emsian section from the US (Road 199 section, Kingston, New York) will be targeted. Strata display Milankovitch cycles to a varying visible degree but spectral analysis of MS with supporting magnetic property tests enables to constrain durations up to an order of magnitude more precise than in the current (2012) Geological Time Scale.

A High-Resolution Biogenic Silica Record From Lake Titicaca, Peru-Bolivia: South American Millennial-Scale Climate Variability From 18-60 Kya

NASA Astrophysics Data System (ADS)

Ekdahl, E. J.; Fritz, S. C.; Stevens, L. R.; Baker, P. A.; Seltzer, G. O.

2004-12-01

Sediments recovered from a deep basin in Lake Titicaca, Peru-Boliva, were analyzed for biogenic silica (BSi) content by extraction of freeze dried sediments in 1% sodium carbonate. Sediments were dated using an age model developed from multiple 14C dates on bulk sediments. The BSi record shows distinct fluctuations in concentration and accumulation rate from 18 to 60 kya. Multi-taper method spectral analysis reveals a significant millennial-scale component to these fluctuations centered at 1370 years. High BSi accumulation rates correlate with enhanced benthic diatom preservation, suggesting that the BSi record is related to variations in lake water level. Modern-day Lake Titicaca lake level and precipitation are strongly related to northern equatorial Atlantic sea surface temperatures, with cooler SSTs related to wetter conditions. Subsequently, the spectral behavior of the GRIP ice core δ 18O record was investigated in order to estimate coherency and linkages between North Atlantic and tropical South American climate. GRIP data exhibit a significant 1370-year spectral peak which comprises approximately 26% of the total variability in the record. Despite a high degree of coherency between millennial-scale periodicities in Lake Titicaca BSi and GRIP δ 18O records, the Lake Titicaca silica record does not show longer term cooling cycles characteristic of D-O cycles found in the GRIP record. Rather, the Lake Titicaca record is highly periodic and more similar in nature to several Antarctic climate proxy records. These results suggest that while South American tropical climate varies in phase with North Atlantic climate, additional forcing mechanisms are manifest in the region which may include tropical Pacific and Southern Ocean variability.

A statistical study on the occurrence of discrete frequencies in the high velocity solar wind and in the magnetosphere

NASA Astrophysics Data System (ADS)

Di Matteo, Simone; Villante, Umberto

2016-04-01

The possible occurrence of oscillations at discrete frequencies in the solar wind and their possible correspondence with magnetospheric field oscillations represent an interesting aspect of the solar wind/magnetopheric research. We analyze a large set of high velocity streams following interplanetary shocks in order to ascertain the possible occurrence of preferential sets of discrete frequencies in the oscillations of the solar wind pressure in such structures. We evaluate, for each event, the power spectrum of the dynamic pressure by means of two methods (Welch and multitaper windowing) and accept the common spectral peaks that also pass a harmonic F-test at the 95% confidence level. We compare these frequencies with those detected at geosynchronous orbit in the magnetospheric field components soon after the manifestation of the corresponding Sudden Impulses.

Evolution of the Climate Continuum from the Mid-Miocene Climatic Optimum to the Present

NASA Astrophysics Data System (ADS)

Aswasereelert, W.; Meyers, S. R.; Hinnov, L. A.; Kelly, D.

2011-12-01

The recognition of orbital rhythms in paleoclimate data has led to a rich understanding of climate evolution during the Neogene and Quaternary. In contrast, changes in stochastic variability associated with the transition from unipolar to bipolar glaciation have received less attention, although the stochastic component likely preserves key insights about climate. In this study, we seek to evaluate the dominance and character of stochastic climate energy since the Middle Miocene Climatic Optimum (~17 Ma). These analyses extend a previous study that suggested diagnostic stochastic responses associated with Northern Hemisphere ice sheet development during the Plio-Pleistocene (Meyers and Hinnov, 2010). A critical and challenging step necessary to conduct the work is the conversion of depth data to time data. We investigate climate proxy datasets using multiple time scale hypotheses, including depth-derived time scales, sedimentologic/geochemical "tuning", minimal orbital tuning, and comprehensive orbital tuning. To extract the stochastic component of climate, and also explore potential relationships between the orbital parameters and paleoclimate response, a number of approaches rooted in Thomson's (1982) multi-taper spectral method (MTM) are applied. Importantly, the MTM technique is capable of separating the spectral "continuum" - a measure of stochastic variability - from the deterministic periodic orbital signals (spectral "lines") preserved in proxy data. Time series analysis of the proxy records using different chronologic approaches allows us to evaluate the sensitivity of our conclusion about stochastic and deterministic orbital processes during the Middle Miocene to present. Moreover, comparison of individual records permits examination of the spatial dependence of the identified climate responses. Meyers, S.R., and Hinnov, L.A. (2010), Northern Hemisphere glaciation and the evolution of Plio-Pleistocene climate noise: Paleoceanography, 25, PA3207, doi:10.1029/2009PA001834. Thomson, D.J. (1982), Spectrum estimation and harmonic analysis: IEEE Proceedings, v. 70, p. 1055-1096.

The Exponent of High-frequency Source Spectral Falloff and Contribution to Source Parameter Estimates

NASA Astrophysics Data System (ADS)

Kiuchi, R.; Mori, J. J.

2015-12-01

As a way to understand the characteristics of the earthquake source, studies of source parameters (such as radiated energy and stress drop) and their scaling are important. In order to estimate source parameters reliably, often we must use appropriate source spectrum models and the omega-square model is most frequently used. In this model, the spectrum is flat in lower frequencies and the falloff is proportional to the angular frequency squared. However, Some studies (e.g. Allmann and Shearer, 2009; Yagi et al., 2012) reported that the exponent of the high frequency falloff is other than -2. Therefore, in this study we estimate the source parameters using a spectral model for which the falloff exponent is not fixed. We analyze the mainshock and larger aftershocks of the 2008 Iwate-Miyagi Nairiku earthquake. Firstly, we calculate the P wave and SH wave spectra using empirical Green functions (EGF) to remove the path effect (such as attenuation) and site effect. For the EGF event, we select a smaller earthquake that is highly-correlated with the target event. In order to obtain the stable results, we calculate the spectral ratios using a multitaper spectrum analysis (Prieto et al., 2009). Then we take a geometric mean from multiple stations. Finally, using the obtained spectra ratios, we perform a grid search to determine the high frequency falloffs, as well as corner frequency of both of events. Our results indicate the high frequency falloff exponent is often less than 2.0. We do not observe any regional, focal mechanism, or depth dependencies for the falloff exponent. In addition, our estimated corner frequencies and falloff exponents are consistent between the P wave and SH wave analysis. In our presentation, we show differences in estimated source parameters using a fixed omega-square model and a model allowing variable high-frequency falloff.

Dynamics of zebra finch and mockingbird vocalizations

NASA Astrophysics Data System (ADS)

Cimenser, Aylin

Along with humans, whales, and bats, three groups of birds which include songbirds (oscines) such as the Zebra Finch (Taeniopygia guttata) and Mockingbird (Mimus polyglottos) are the only creatures known to learn sounds by imitation. Numerous similarities between human and songbird vocalizations exist and, recently, it has been shown that Zebra Finch in particular possesses a gene, FoxP2, known to be involved in human language. This thesis investigates song development in Zebra Finches, as well as the temporal dynamics of song in Mockingbirds. Zebra Finches have long been the system of choice for studying vocal development, ontogeny, and complexity in birdsong. Physicists find them intriguing because the spectrally complex vocalizations of the Zebra Finch can exhibit sudden transitions to chaotic dynamics, period doubling & mode-locking phenomena. Mockingbirds, by contrast, provide an ideal system to examine the richness of an avian repertoire, since these musically versatile songbirds typically know upwards of 200 songs. To analyse birdsong data, we have developed a novel clustering algorithm that can be applied to the bird's syllables, tracing their dynamics back to the earliest stages of vocal development. To characterize birdsong we have used Fourier techniques, based upon multitaper spectral analysis, to optimally work around the constraints imposed by (Heisenberg's) time-frequency uncertainty principle. Furthermore, estimates that provide optimal compromise between frequency and temporal resolution have beautiful connections with solutions to the Helmholtz wave equation in prolate spheroidal coordinates. We have used this connection to provide firm foundation for certain heuristics used in the literature to compute associated spectral derivatives and supply a pedagogical account here in this thesis. They are of interest because spectral derivatives emphasize sudden changes in the dynamics of the underlying phenomenon, and often provide a nice way to visualize such dynamics. Our Zebra Finch data consist of continuous recordings of six tutored birds from the early, plastic stages of sound production to the development of fully crystallized mature song. Our analysis reveals that well before the Zebra Finch hears adult song, identifiably distinct clusters are observable for all birds in the same regions of feature space. (Abstract shortened by UMI.)

Tidally induced turbulence in the Bermuda underwater cave-system

NASA Astrophysics Data System (ADS)

Molodtsov, S.; Anis, A.; Iliffe, T. M.

2016-02-01

This study presents results from field measurements of turbulence made in Bermuda's underwater cave-system. To the best of our knowledge, this is the first time that turbulence velocity measurements have been taken in an underwater cave-system. Water currents in caves are unaffected by surface waves and thus provide a unique opportunity to obtain clear signals of tidally induced turbulence. An acoustic Doppler velocimeter and acoustic Doppler current profiler were deployed in several cave locations during a period of six days. Power spectral density (PSD) of velocity fluctuations was estimated using the multitaper power spectral method. Turbulence kinetic energy dissipation rates, ɛ, were calculated based on the PSD and were found to exhibit a clear -5/3 slope within the inertial subrange. Measurement periods covered full diurnal cycles and estimates of ɛ showed a strong correlation with the tide phase with values up to 10-3 W/kg during peak ebb and flood (horizontal velocities up to 0.35 m/s). Furthermore, ɛ was found to closely follow the wall boundary layer parametrization, ɛ = u*3/(ᴋz), where u* is the friction velocity, ᴋ is von Karman's constant, and z is the height above the bed.

Economic cycles and their synchronization: Spectral analysis of macroeconomic series from Italy, The Netherlands, and the UK

NASA Astrophysics Data System (ADS)

Sella, Lisa; Vivaldo, Gianna; Ghil, Michael; Groth, Andreas

2010-05-01

The present work applies several advanced spectral methods (Ghil et al., Rev. Geophys., 2002) to the analysis of macroeconomic fluctuations in Italy, The Netherlands, and the United Kingdom. These methods provide valuable time-and-frequency-domain tools that complement traditional time-domain analysis, and are thus fairly well known by now in the geosciences and life sciences, but not yet widespread in quantitative economics. In particular, they enable the identification and characterization of nonlinear trends and dominant cycles --- including low-frequency and seasonal components --- that characterize the behavior of each time series. We explore five fundamental indicators of the real (i.e., non-monetary), aggregate economy --- namely gross domestic product (GDP), consumption, fixed investments, exports and imports --- in a univariate as well as multivariate setting. A single-channel analysis by means of three independent spectral methods --- singular spectrum analysis (SSA), the multi-taper method (MTM), and the maximum-entropy method (MEM) --- reveals very similar near-annual cycles, as well as several longer periodicities, in the macroeconomic indicators of all the countries analyzed. Since each indicator represents different features of an economic system, we combine them to infer if common oscillatory modes are present, either among different indicators within the same country or among the same indicators across different countries. Multichannel-SSA (M-SSA) reinforces the previous results, and shows that the common modes agree in character with solutions of a non-equilibrium dynamic model (NEDyM) that produces endogenous business cycles (Hallegatte et al., JEBO, 2008). The presence of these modes in NEDyM results from adjustment delays and other nonequilibrium effects that were added to a neoclassical Solow (Q. J. Econ., 1956) growth model. Their confirmation by the present analysis has important consequences for the net impact of natural disasters on the economy of a country: Hallegatte and Ghil (Ecol. Econ., 2008) have shown that the presence of business cycles modifies substantially this impact with respect to their impact on an economy in or near equilibrium. The present work concludes with a study of the synchronization of economic fluctuations, which follows a similar study of macroeconomic indicators for the United States, presented in a nearby poster. Since business cycles are not country-specific phenomena, but show common characteristics across countries, our aim is to uncover hidden global behavior across the European economies (cf. Mazzi and Savio, Macmillan, 2006).

Evaluation of a novel median power spectrogram for seizure detection by non-neurophysiologists.

PubMed

Yan, Peter; Melman, Tamar; Yan, Sherry; Otgonsuren, Munkhzul; Grinspan, Zachary

2017-08-01

(1) To evaluate how well resident physicians use a novel EEG spectral analysis tool (the median power spectrogram; MPS) to detect seizures. (2) To assess the capability of the MPS to identify different seizure types. 120 EEG records from children with intractable seizures were converted to MPS by taking the median power across leads and using multi-taper spectral estimation. Twelve blinded neurology residents were trained to interpret the spectrogram with a five-minute video tutorial and post-test. Two residents independently assessed each set for presence of seizures. Their performance was compared to seizures identified using conventional EEG. Two blinded neurologists separately reviewed the EEGs and spectrograms to independently categorize the seizures. Their results were used to determine the spectrogram's capability to reveal seizures and visualize different seizure types for the user. Three key MPS features distinguished seizures from inter-ictal background: power difference relative to background, down-sloping resonance bands, and power in high frequencies. Using these features, residents identified seizures with 77% sensitivity and 72% specificity. 86% (51/59) of focal seizures and 81% (22/27) of generalized seizures were detected by at least one resident. Missed seizures included brief (<60s) seizures, tonic seizures, seizures with predominant delta (0-4Hz) activity, and seizures evident primarily in supplementary low temporal leads. The MPS is a novel qEEG modality that requires minimal training to interpret. It enables physicians without extensive neurophysiology training to identify seizures with sensitivity and specificity comparable to more complex multi-modal qEEG displays. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Evidence of solar activity and El Niño signals in tree rings of Araucaria araucana and A. angustifolia in South America

NASA Astrophysics Data System (ADS)

Perone, A.; Lombardi, F.; Marchetti, M.; Tognetti, R.; Lasserre, B.

2016-10-01

Tree rings reveal climatic variations through years, but also the effect of solar activity in influencing the climate on a large scale. In order to investigate the role of solar cycles on climatic variability and to analyse their influences on tree growth, we focused on tree-ring chronologies of Araucaria angustifolia and Araucaria araucana in four study areas: Irati and Curitiba in Brazil, Caviahue in Chile, and Tolhuaca in Argentina. We obtained an average tree-ring chronology of 218, 117, 439, and 849 years for these areas, respectively. Particularly, the older chronologies also included the period of the Maunder and Dalton minima. To identify periodicities and trends observable in tree growth, the time series were analysed using spectral, wavelet and cross-wavelet techniques. Analysis based on the Multitaper method of annual growth rates identified 2 cycles with periodicities of 11 (Schwebe cycle) and 5.5 years (second harmonic of Schwebe cycle). In the Chilean and Argentinian sites, significant agreement between the time series of tree rings and the 11-year solar cycle was found during the periods of maximum solar activity. Results also showed oscillation with periods of 2-7 years, probably induced by local environmental variations, and possibly also related to the El-Niño events. Moreover, the Morlet complex wavelet analysis was applied to study the most relevant variability factors affecting tree-ring time series. Finally, we applied the cross-wavelet spectral analysis to evaluate the time lags between tree-ring and sunspot-number time series, as well as for the interaction between tree rings, the Southern Oscillation Index (SOI) and temperature and precipitation. Trees sampled in Chile and Argentina showed more evident responses of fluctuations in tree-ring time series to the variations of short and long periodicities in comparison with the Brazilian ones. These results provided new evidence on the solar activity-climate pattern-tree ring connections over centuries.

Robust power spectral estimation for EEG data

PubMed Central

Melman, Tamar; Victor, Jonathan D.

2016-01-01

Background Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. New method Using the multitaper method[1] as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Results Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. Comparison to existing method The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. Conclusion In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. PMID:27102041

Robust power spectral estimation for EEG data.

PubMed

Melman, Tamar; Victor, Jonathan D

2016-08-01

Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.

Assisted entry mitigates text messaging-based driving detriment.

PubMed

Sawyer, Benjamin D; Hancock, Peter A

2012-01-01

Previous research using cell phones indicates that manual manipulation is not a principal component of text messaging relating driving detriment. This paper suggests that manipulation of a phone in conjunction with the cognitive need to compose the message itself co-act to contribute to driving degradation. This being so, drivers sending text messages might experience reduced interference to the driving task if the text messaging itself were assisted through the predictive T9 system. We evaluated undergraduate drivers in a simulator who drove and texted using either Assisted Text entry, via Nokia's T9 system, or unassisted entry via the multitap interface. Results supported the superiority of the T9 system over the multitap system implying that specific assistive technologies can modulate the degradation of capacity which texting tragically induces.

Nonlinear Dynamics, Poor Data, and What to Make of Them?

NASA Astrophysics Data System (ADS)

Ghil, M.; Zaliapin, I. V.

2005-12-01

The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict variability in the geosciences. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this talk we will describe the connections between time series analysis and nonlinear dynamics, discuss signal-to-noise enhancement, and present some of the novel methods for spectral analysis. These fall into two broad categories: (i) methods that try to ferret out regularities of the time series; and (ii) methods aimed at describing the characteristics of irregular processes. The former include singular-spectrum analysis (SSA), the multi-taper method (MTM), and the maximum-entropy method (MEM). The various steps, as well as the advantages and disadvantages of these methods, will be illustrated by their application to several important climatic time series, such as the Southern Oscillation Index (SOI), paleoclimatic time series, and instrumental temperature time series. The SOI index captures major features of interannual climate variability and is used extensively in its prediction. The other time series cover interdecadal and millennial time scales. The second category includes the calculation of fractional dimension, leading Lyapunov exponents, and Hurst exponents. More recently, multi-trend analysis (MTA), binary-decomposition analysis (BDA), and related methods have attempted to describe the structure of time series that include both regular and irregular components. Within the time available, I will try to give a feeling for how these methods work, and how well.

Evidence for a possible modern and mid-Holocene solar influence on climate from Lake Titicaca, South America

NASA Astrophysics Data System (ADS)

Theissen, K. M.; Dunbar, R. B.

2005-12-01

In tropical regions, there are few paleoclimate archives with the necessary resolution to investigate climate variability at interannual-to-decadal timescales prior to the onset of the instrumental record. Interannual variability associated with the El Niño Southern Oscillation (ENSO) is well documented in the instrumental record and the importance of the precessional forcing of millennial variability has been established in studies of tropical paleoclimate records. In contrast, decade-to-century variability is still poorly understood. Here, we examine interannual to decadal variability in the northern Altiplano of South America using digital image analysis of a floating interval of varved sediments of middle Holocene age (~6160-6310 yr BP) from Lake Titicaca. Multi-taper method (MTM) and wavelet frequency-domain analyses were performed on a time series generated from a gray-scaled digital image of the mm-thick laminations. Our results indicate significant power at a decadal periodicity (10-12 years) associated with the Schwabe cycle of solar activity. Frequency-domain analysis also indicates power at 2-2.5 year periodicities associated with ENSO. Similarly, spectral analysis of a 75 year instrumental record of Titicaca lake level shows significant power at both solar and ENSO periodicities. Although both of the examined records are short, our results imply that during both the mid-Holocene and modern times, solar and ENSO variability may have contributed to high frequency climate fluctuations over the northern Altiplano. We suspect that solar influence on large-scale atmospheric circulation features may account for the decadal variability in the mid-Holocene and present-day water balance of the Altiplano.

Milankovitch Cyclicity in the Eocene Green River Formation of Colorado and Wyoming

NASA Astrophysics Data System (ADS)

Machlus, M.; Olsen, P. E.; Christie-Blick, N.; Hemming, S. R.

2001-12-01

The Eocene Green River Formation is a classic example of cyclic lacustrine sediments. Following Bradley (1929, U.S.G.S. Prof. Paper 158-E), many descriptive studies suggested precession and eccentricity as the probable climatic forcing to produce the cyclic pattern. Here we report spectral analysis results that confirm this hypothesis. Furthermore, we have identified the presence of a surprisingly large amplitude obliquity cycle, the long-period eccentricity cycle (400 k.y.) and the long period modulators of obliquity. Spectral analyses of data from Colorado were undertaken on an outcrop section and core data using two different proxies for lake depth. In a section measured in the west Piceance Creek basin, three lithologies (ranks) were used as a proxy for relative water depth, from relatively shallow to deep water: laminated marlstones; microlaminated, light-colored oil-shales; and microlaminated black oil shales. A multi-tapered spectrum of the 190-m-thick record in the depth domain shows significant peaks at periods of 2.1, 3.4, 12 and 39 m. These are interpreted as the precession, obliquity and eccentricity cycles. The precession cycle confirms Bradley's independent estimate of 2.4 m per 20 k.y. cycle, based on varve counts at the same location. A high-amplitude, continuous 3.4 m (obliquity) cycle exists in the evolutive spectrum of this record. A second spectral analysis of an oil-shale-yield record was made on a 530 m core near the basin depocenter. This record includes the time-equivalent of the outcrop section, spans a longer interval of time, and has a higher sedimentation rate. Peaks are found at 5, 10, 25 and 79 m. Again, the probable obliquity peak, at 10 m, is continuous along the record. Initial tuning of this record to a 39.9 k.y. cosine wave improves the resolution of the precession, short and long eccentricity cycles. Spectral analysis of oil shale yield and sonic velocity data of cores from the Green River basin, Wyoming, gives similar results. Spectral peaks at 6, 13, 31 and 122 m appear mainly in the Tipton and the Wilkins Peak members. The correlation between oil shale yield, lithology and relative water depth was examined in the upper part of the Wilkins Peak Member and the Lower part of the Laney Member. The succession from microlaminated black oil shale to laminated micrite corresponds with documented lateral changes in facies from deep to shallow environments, thus confirming the use of these facies as relative water-depth proxies. Furthermore, the upsection record of oil shale yields correlates with these facies, with higher yields corresponding to deeper water facies. This correlation supports the use of the oil shale yield record as a proxy for short-term lake-level changes, and therefore a proxy for climate. The spectral analysis results from both basins show the importance of the obliquity cycle in these continental records. This cycle cannot be identified by cycle-counting, and therefore was not previously recognized. Earlier published attempts at spectral analysis of short records from the Piceance Creek and Uinta basins misinterpreted the observed cycles. This is the first time both the obliquity cycle and the long-term eccentricity cycle have been identified in the Green River and Piceance Creek basins.

Effect of windowing on lithosphere elastic thickness estimates obtained via the coherence method: Results from northern South America

NASA Astrophysics Data System (ADS)

Ojeda, GermáN. Y.; Whitman, Dean

2002-11-01

The effective elastic thickness (Te) of the lithosphere is a parameter that describes the flexural strength of a plate. A method routinely used to quantify this parameter is to calculate the coherence between the two-dimensional gravity and topography spectra. Prior to spectra calculation, data grids must be "windowed" in order to avoid edge effects. We investigated the sensitivity of Te estimates obtained via the coherence method to mirroring, Hanning and multitaper windowing techniques on synthetic data as well as on data from northern South America. These analyses suggest that the choice of windowing technique plays an important role in Te estimates and may result in discrepancies of several kilometers depending on the selected windowing method. Te results from mirrored grids tend to be greater than those from Hanning smoothed or multitapered grids. Results obtained from mirrored grids are likely to be over-estimates. This effect may be due to artificial long wavelengths introduced into the data at the time of mirroring. Coherence estimates obtained from three subareas in northern South America indicate that the average effective elastic thickness is in the range of 29-30 km, according to Hanning and multitaper windowed data. Lateral variations across the study area could not be unequivocally determined from this study. We suggest that the resolution of the coherence method does not permit evaluation of small (i.e., ˜5 km), local Te variations. However, the efficiency and robustness of the coherence method in rendering continent-scale estimates of elastic thickness has been confirmed.

FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data.

PubMed

Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.

[Shaping ability of multi-taper nickel-titanium files in simulated resin curved root canal].

PubMed

Luo, Hong-Xia; Huang, Ding-Ming; Jia, Liu-He; Luo, Shi-Gao; Gao, Xiao-Jie; Tan, Hong; Zhou, Xue-Dong

2006-08-01

To compare the shaping ability of ISO standard stainless steel K files and multi-taper ProTaper nickel-titanium files in simulated resin curved root canals. METHODS Thirty simulated resin root canals were randomly divided into three groups and prepared by stainless steel K files, hand ProTaper, rotary ProTaper, respectively. The amount of material removed from inner and outer wall and canal width after canal preparation was measured, while the canal curvature before and after canal preparation and canals aberrations were recorded. The stainless steel K files removed more material than hand ProTaper and rotary ProTaper at the outer side of apex and inner side of curvature (P < 0.05). The mean degree of straightening in stainless steel K files group was significantly bigger than in ProTaper group (P < 0.05). The canals prepared by ProTaper had no evident aberration. The shaping ability of ProTaper is better than stainless steel K files.

Optimal Bandwidth for Multitaper Spectrum Estimation

DOE PAGES

Haley, Charlotte L.; Anitescu, Mihai

2017-07-04

A systematic method for bandwidth parameter selection is desired for Thomson multitaper spectrum estimation. We give a method for determining the optimal bandwidth based on a mean squared error (MSE) criterion. When the true spectrum has a second-order Taylor series expansion, one can express quadratic local bias as a function of the curvature of the spectrum, which can be estimated by using a simple spline approximation. This is combined with a variance estimate, obtained by jackknifing over individual spectrum estimates, to produce an estimated MSE for the log spectrum estimate for each choice of time-bandwidth product. The bandwidth that minimizesmore » the estimated MSE then gives the desired spectrum estimate. Additionally, the bandwidth obtained using our method is also optimal for cepstrum estimates. We give an example of a damped oscillatory (Lorentzian) process in which the approximate optimal bandwidth can be written as a function of the damping parameter. Furthermore, the true optimal bandwidth agrees well with that given by minimizing estimated the MSE in these examples.« less

Spectral Estimation Techniques for time series with Long Gaps: Applications to Paleomagnetism and Geomagnetic Depth Sounding

NASA Astrophysics Data System (ADS)

Smith-Boughner, Lindsay

Many Earth systems cannot be studied directly. One cannot measure the velocities of convecting fluid in the Earth's core but can measure the magnetic field generated by these motions on the surface. Examining how the magnetic field changes over long periods of time, using power spectral density estimation provides insight into the dynamics driving the system. The changes in the magnetic field can also be used to study Earth properties - variations in magnetic fields outside of Earth like the ring-current induce currents to flow in the Earth, generating magnetic fields. Estimating the transfer function between the external changes and the induced response characterizes the electromagnetic response of the Earth. From this response inferences can be made about the electrical conductivity of the Earth. However, these types of time series, and many others have long breaks in the record with no samples available and limit the analysis. Standard methods require interpolation or section averaging, with associated problems of introducing bias or reducing the frequency resolution. Extending the methods of Fodor and Stark (2000), who adapt a set of orthogonal multi-tapers to compensate for breaks in sampling- an algorithm and software package for applying these techniques is developed. Methods of empirically estimating the average transfer function of a set of tapers and confidence intervals are also tested. These methods are extended for cross-spectral, coherence and transfer function estimation in the presence of noise. With these methods, new analysis of a highly interrupted ocean sediment core from the Oligocene (Hartl et al., 1993) reveals a quasi-periodic signal in the calibrated paleointensity time series at 2.5 cpMy. The power in the magnetic field during this period appears to be dominated by reversal rate processes with less overall power than the early Oligocene. Previous analysis of the early Oligocene by Constable et al. (1998) detected a signal near 8 cpMy. These results suggest that a strong magnetic field inhibits reversals and has more variability in shorter term field changes. Using over 9 years of data from the CHAMP low-Earth orbiting magnetic satellite and the techniques developed here, more robust estimates of the electromagnetic response of the Earth can be made. The tapers adapted for gaps provide flexibility to study the effects of local time, storm conditions on Earth's 1-D electromagnetic response as well as providing robust estimates of the C-response at longer periods than previous satellite studies.

A Prospective Study of Age-dependent Changes in Propofol-induced Electroencephalogram Oscillations in Children.

PubMed

Lee, Johanna M; Akeju, Oluwaseun; Terzakis, Kristina; Pavone, Kara J; Deng, Hao; Houle, Timothy T; Firth, Paul G; Shank, Erik S; Brown, Emery N; Purdon, Patrick L

2017-08-01

In adults, frontal electroencephalogram patterns observed during propofol-induced unconsciousness consist of slow oscillations (0.1 to 1 Hz) and coherent alpha oscillations (8 to 13 Hz). Given that the nervous system undergoes significant changes during development, anesthesia-induced electroencephalogram oscillations in children may differ from those observed in adults. Therefore, we investigated age-related changes in frontal electroencephalogram power spectra and coherence during propofol-induced unconsciousness. We analyzed electroencephalogram data recorded during propofol-induced unconsciousness in patients between 0 and 21 yr of age (n = 97), using multitaper spectral and coherence methods. We characterized power and coherence as a function of age using multiple linear regression analysis and within four age groups: 4 months to 1 yr old (n = 4), greater than 1 to 7 yr old (n = 16), greater than 7 to 14 yr old (n = 30), and greater than 14 to 21 yr old (n = 47). Total electroencephalogram power (0.1 to 40 Hz) peaked at approximately 8 yr old and subsequently declined with increasing age. For patients greater than 1 yr old, the propofol-induced electroencephalogram structure was qualitatively similar regardless of age, featuring slow and coherent alpha oscillations. For patients under 1 yr of age, frontal alpha oscillations were not coherent. Neurodevelopmental processes that occur throughout childhood, including thalamocortical development, may underlie age-dependent changes in electroencephalogram power and coherence during anesthesia. These age-dependent anesthesia-induced electroencephalogram oscillations suggest a more principled approach to monitoring brain states in pediatric patients.

The August 2011 Virginia and Colorado Earthquake Sequences: Does Stress Drop Depend on Strain Rate?

NASA Astrophysics Data System (ADS)

Abercrombie, R. E.; Viegas, G.

2011-12-01

Our preliminary analysis of the August 2011 Virginia earthquake sequence finds the earthquakes to have high stress drops, similar to those of recent earthquakes in NE USA, while those of the August 2011 Trinidad, Colorado, earthquakes are moderate - in between those typical of interplate (California) and the east coast. These earthquakes provide an unprecedented opportunity to study such source differences in detail, and hence improve our estimates of seismic hazard. Previously, the lack of well-recorded earthquakes in the eastern USA severely limited our resolution of the source processes and hence the expected ground accelerations. Our preliminary findings are consistent with the idea that earthquake faults strengthen during longer recurrence times and intraplate faults fail at higher stress (and produce higher ground accelerations) than their interplate counterparts. We use the empirical Green's function (EGF) method to calculate source parameters for the Virginia mainshock and three larger aftershocks, and for the Trinidad mainshock and two larger foreshocks using IRIS-available stations. We select time windows around the direct P and S waves at the closest stations and calculate spectral ratios and source time functions using the multi-taper spectral approach (eg. Viegas et al., JGR 2010). Our preliminary results show that the Virginia sequence has high stress drops (~100-200 MPa, using Madariaga (1976) model), and the Colorado sequence has moderate stress drops (~20 MPa). These numbers are consistent with previous work in the regions, for example the Au Sable Forks (2002) earthquake, and the 2010 Germantown (MD) earthquake. We also calculate the radiated seismic energy and find the energy/moment ratio to be high for the Virginia earthquakes, and moderate for the Colorado sequence. We observe no evidence of a breakdown in constant stress drop scaling in this limited number of earthquakes. We extend our analysis to a larger number of earthquakes and stations. We calculate uncertainties in all our measurements, and also consider carefully the effects of variation in available bandwidth in order to improve our constraints on the source parameters.

FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

PubMed Central

Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages. PMID:21253357

Tunable and reconfigurable microwave filter by use of a Bragg-grating-based acousto-optic superlattice modulator.

PubMed

Delgado-Pinar, M; Mora, J; Díez, A; Andrés, M V; Ortega, B; Capmany, J

2005-01-01

We present an all-optical novel configuration for implementing multitap transversal filters by use of a broadband source sliced by fiber Bragg grating arrays generated by propagating an acoustic wave along a strong uniform fiber Bragg grating. The tunability and reconfigurability of the microwave filter are demonstrated.

The Dynamic Photometric Stereo Method Using a Multi-Tap CMOS Image Sensor.

PubMed

Yoda, Takuya; Nagahara, Hajime; Taniguchi, Rin-Ichiro; Kagawa, Keiichiro; Yasutomi, Keita; Kawahito, Shoji

2018-03-05

The photometric stereo method enables estimation of surface normals from images that have been captured using different but known lighting directions. The classical photometric stereo method requires at least three images to determine the normals in a given scene. However, this method cannot be applied to dynamic scenes because it is assumed that the scene remains static while the required images are captured. In this work, we present a dynamic photometric stereo method for estimation of the surface normals in a dynamic scene. We use a multi-tap complementary metal-oxide-semiconductor (CMOS) image sensor to capture the input images required for the proposed photometric stereo method. This image sensor can divide the electrons from the photodiode from a single pixel into the different taps of the exposures and can thus capture multiple images under different lighting conditions with almost identical timing. We implemented a camera lighting system and created a software application to enable estimation of the normal map in real time. We also evaluated the accuracy of the estimated surface normals and demonstrated that our proposed method can estimate the surface normals of dynamic scenes.

Seismic tomography of the southern California crust based on spectral-element and adjoint methods

NASA Astrophysics Data System (ADS)

Tape, Carl; Liu, Qinya; Maggi, Alessia; Tromp, Jeroen

2010-01-01

We iteratively improve a 3-D tomographic model of the southern California crust using numerical simulations of seismic wave propagation based on a spectral-element method (SEM) in combination with an adjoint method. The initial 3-D model is provided by the Southern California Earthquake Center. The data set comprises three-component seismic waveforms (i.e. both body and surface waves), filtered over the period range 2-30 s, from 143 local earthquakes recorded by a network of 203 stations. Time windows for measurements are automatically selected by the FLEXWIN algorithm. The misfit function in the tomographic inversion is based on frequency-dependent multitaper traveltime differences. The gradient of the misfit function and related finite-frequency sensitivity kernels for each earthquake are computed using an adjoint technique. The kernels are combined using a source subspace projection method to compute a model update at each iteration of a gradient-based minimization algorithm. The inversion involved 16 iterations, which required 6800 wavefield simulations. The new crustal model, m16, is described in terms of independent shear (VS) and bulk-sound (VB) wave speed variations. It exhibits strong heterogeneity, including local changes of +/-30 per cent with respect to the initial 3-D model. The model reveals several features that relate to geological observations, such as sedimentary basins, exhumed batholiths, and contrasting lithologies across faults. The quality of the new model is validated by quantifying waveform misfits of full-length seismograms from 91 earthquakes that were not used in the tomographic inversion. The new model provides more accurate synthetic seismograms that will benefit seismic hazard assessment.

The Dynamic Photometric Stereo Method Using a Multi-Tap CMOS Image Sensor †

PubMed Central

Yoda, Takuya; Nagahara, Hajime; Taniguchi, Rin-ichiro; Kagawa, Keiichiro; Yasutomi, Keita; Kawahito, Shoji

2018-01-01

The photometric stereo method enables estimation of surface normals from images that have been captured using different but known lighting directions. The classical photometric stereo method requires at least three images to determine the normals in a given scene. However, this method cannot be applied to dynamic scenes because it is assumed that the scene remains static while the required images are captured. In this work, we present a dynamic photometric stereo method for estimation of the surface normals in a dynamic scene. We use a multi-tap complementary metal-oxide-semiconductor (CMOS) image sensor to capture the input images required for the proposed photometric stereo method. This image sensor can divide the electrons from the photodiode from a single pixel into the different taps of the exposures and can thus capture multiple images under different lighting conditions with almost identical timing. We implemented a camera lighting system and created a software application to enable estimation of the normal map in real time. We also evaluated the accuracy of the estimated surface normals and demonstrated that our proposed method can estimate the surface normals of dynamic scenes. PMID:29510599

Programed Instruction for Selected CIC Watch Officer Tasks. 2. Evaluation of the Audio Notebook in the Teaching of the Allied Naval Signal Book.

ERIC Educational Resources Information Center

Brock, John F.

The research evaluated oral program instruction used with a multitape recorder, the audio notebook, as a means of promoting adaptation to student differences and flexibility in instructional scheduling. Use of the Allied Naval Signal Book required by the CIC (Combat Information Center) watch officer position was programed for the audio notebook in…

Estimates of effective elastic thickness of oceanic lithosphere using model including surface and subsurface loads and effective elastic thickness of subduction zones

NASA Astrophysics Data System (ADS)

Yang, A.; Yongtao, F.

2016-12-01

The effective elastic thickness (Te) is an important parameter that characterizes the long term strength of the lithosphere, which has great significance on understanding the mechanical properties and evolution of the lithosphere. In contrast with many controversies regarding elastic thickness of continent lithosphere, the Te of oceanic lithosphere is thought to be in a simple way that is dependent on the age of the plate. However, rescent studies show that there is no simple relationship between Te and age at time of loading for both seamounts and subduction zones. As subsurface loading is very importand and has large influence in the estimate of Te for continent lithosphere, and many oceanic features such as subduction zones also have considerable subsurface loading. We introduce the method to estimate the effective elastic thickness of oceanic lithosphere using model including surface and subsurface loads by using free-air gravity anomaly and bathymetric data, together with a moving window admittance technique (MWAT). We use the multitaper spectral estimation method to calculate the power spectral density. Through tests with synthetic subduction zone like bathymetry and gravity data show that the Te can be recovered in an accurance similar to that in the continent and there is also a trade-off between spatial resolution and variance for different window sizes. We estimate Te of many subduction zones (Peru-Chile trench, Middle America trench, Caribbean trench, Kuril-Japan trench, Mariana trench, Tonga trench, Java trench, Ryukyu-Philippine trench) with an age range of 0-160 Myr to reassess the relationship between elastic thickness and the age of the lithosphere at the time of loading. The results do not show a simple relationship between Te and age.

Some considerations on the vibrational environment of the DSC-DCMIX1 experiment onboard ISS

NASA Astrophysics Data System (ADS)

Jurado, R.; Gavaldà, Jna.; Simón, M. J.; Pallarés, J.; Laverón-Simavilla, A.; Ruiz, X.; Shevtsova, V.

2016-12-01

The present work attempts to characterize the accelerometric environment of the DSC-DCMIX1 thermodiffusion experiment carried out in the International Space Station, from November 7th 2011 until January 16th 2012. Quasi-steady and vibrational/transient data coming from MAMS and SAMS2 sensors have been downloaded from the database of the PIMS NASA website. To be as exhaustive as possible, simultaneous digital signals coming from different SAMS2 sensors located in the Destiny and Columbus modules have also been considered. In order to detect orbital adjustments, dockings, undockings, as well as, quiescent periods, when the experiment runs were active, we have used the quasi-steady eight hours averaged (XA, YA and ZA) acceleration functions as well as the eight hours RMS ones. To determine the spectral contents of the different signals the Thomson multitaper and Welch methods have been used. On the other hand, to suppress the high levels of noise always existing in the raw SAMS2 signals, denoising techniques have been preferred for comparative reboostings considerations. Finally, the RMS values for specific 1/3 octave frequency bands showed that the International Space Station vibratory limit requirements have not been totally accomplished during both quiescent periods and strong disturbances, specially in the low frequency range.

A Picea crassifolia Tree-Ring Width-Based Temperature Reconstruction for the Mt. Dongda Region, Northwest China, and Its Relationship to Large-Scale Climate Forcing.

PubMed

Liu, Yu; Sun, Changfeng; Li, Qiang; Cai, Qiufang

2016-01-01

The historical May-October mean temperature since 1831 was reconstructed based on tree-ring width of Qinghai spruce (Picea crassifolia Kom.) collected on Mt. Dongda, North of the Hexi Corridor in Northwest China. The regression model explained 46.6% of the variance of the instrumentally observed temperature. The cold periods in the reconstruction were 1831-1889, 1894-1901, 1908-1934 and 1950-1952, and the warm periods were 1890-1893, 1902-1907, 1935-1949 and 1953-2011. During the instrumental period (1951-2011), an obvious warming trend appeared in the last twenty years. The reconstruction displayed similar patterns to a temperature reconstruction from the east-central Tibetan Plateau at the inter-decadal timescale, indicating that the temperature reconstruction in this study was a reliable proxy for Northwest China. It was also found that the reconstruction series had good consistency with the Northern Hemisphere temperature at a decadal timescale. Multi-taper method spectral analysis detected some low- and high-frequency cycles (2.3-2.4-year, 2.8-year, 3.4-3.6-year, 5.0-year, 9.9-year and 27.0-year). Combining these cycles, the relationship of the low-frequency change with the Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Southern Oscillation (SO) suggested that the reconstructed temperature variations may be related to large-scale atmospheric-oceanic variations. Major volcanic eruptions were partly reflected in the reconstructed temperatures after high-pass filtering; these events promoted anomalous cooling in this region. The results of this study not only provide new information for assessing the long-term temperature changes in the Hexi Corridor of Northwest China, but also further demonstrate the effects of large-scale atmospheric-oceanic circulation on climate change in Northwest China.

Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions.

PubMed

Hu, Yue; Tu, Xiaotong; Li, Fucai; Meng, Guang

2018-01-07

Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.

Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions

PubMed Central

Li, Fucai; Meng, Guang

2018-01-01

Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults. PMID:29316668

SEISMIC SOURCE SCALING AND DISCRIMINATION IN DIVERSE TECTONIC ENVIRONMENTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abercrombie, R E; Mayeda, K; Walter, W R

2007-07-10

The objectives of this study are to improve low-magnitude regional seismic discrimination by performing a thorough investigation of earthquake source scaling using diverse, high-quality datasets from varied tectonic regions. Local-to-regional high-frequency discrimination requires an estimate of how earthquakes scale with size. Walter and Taylor (2002) developed the MDAC (Magnitude and Distance Amplitude Corrections) method to empirically account for these effects through regional calibration. The accuracy of these corrections has a direct impact on our ability to identify clandestine explosions in the broad regional areas characterized by low seismicity. Unfortunately our knowledge of source scaling at small magnitudes (i.e., m{sub b}more » < {approx}4.0) is poorly resolved. It is not clear whether different studies obtain contradictory results because they analyze different earthquakes, or because they use different methods. Even in regions that are well studied, such as test sites or areas of high seismicity, we still rely on empirical scaling relations derived from studies taken from half-way around the world at inter-plate regions. We investigate earthquake sources and scaling from different tectonic settings, comparing direct and coda wave analysis methods. We begin by developing and improving the two different methods, and then in future years we will apply them both to each set of earthquakes. Analysis of locally recorded, direct waves from events is intuitively the simplest way of obtaining accurate source parameters, as these waves have been least affected by travel through the earth. But there are only a limited number of earthquakes that are recorded locally, by sufficient stations to give good azimuthal coverage, and have very closely located smaller earthquakes that can be used as an empirical Green's function (EGF) to remove path effects. In contrast, coda waves average radiation from all directions so single-station records should be adequate, and previous work suggests that the requirements for the EGF event are much less stringent. We can study more earthquakes using the coda-wave methods, while using direct wave methods for the best recorded subset of events so as to investigate any differences between the results of the two approaches. Finding 'perfect' EGF events for direct wave analysis is difficult, as is ascertaining the quality of a particular EGF event. We develop a multi-taper method to obtain time-domain source-time-functions by frequency division. If an earthquake and EGF event pair are able to produce a clear, time-domain source pulse then we accept the EGF event. We then model the spectral (amplitude) ratio to determine source parameters from both direct P and S waves. We use the well-recorded sequence of aftershocks of the M5 Au Sable Forks, NY, earthquake to test the method and also to obtain some of the first accurate source parameters for small earthquakes in eastern North America. We find that the stress drops are high, confirming previous work suggesting that intraplate continental earthquakes have higher stress drops than events at plate boundaries. We simplify and improve the coda wave analysis method by calculating spectral ratios between different sized earthquakes. We first compare spectral ratio performance between local and near-regional S and coda waves in the San Francisco Bay region for moderate-sized events. The average spectral ratio standard deviations using coda are {approx}0.05 to 0.12, roughly a factor of 3 smaller than direct S-waves for 0.2 < f < 15.0 Hz. Also, direct wave analysis requires collocated pairs of earthquakes whereas the event-pairs (Green's function and target events) can be separated by {approx}25 km for coda amplitudes without any appreciable degradation. We then apply coda spectral ratio method to the 1999 Hector Mine mainshock (M{sub w} 7.0, Mojave Desert) and its larger aftershocks. We observe a clear departure from self-similarity, consistent with previous studies using similar regional datasets.« less

Geochemistry of Slow-Growing Corals: Reconstructing Sea Surface Temperature, Salinity and the North Atlantic Oscillation

DTIC Science & Technology

2007-06-01

foraminifera, gastropods , and scaphopods) has been expressed as [Grossman and Ku, 1986]: 21 60 - 60w = -0.23 * (SST) +4.75 Eqn. (1) Slow growing corals...along the southeastern edge of the platform off John Smith’s Bay at 16m depth. (Figure adapted from World Ocean Circulation Experiment Newsletter...Atlantic Oscillation - Regional Temperatures and Precipitation, Science, 269, 676-679, 1995. Huybers, P., Multi-taper method coherence using adaptive

A two-stage spectrum sensing scheme based on energy detection and a novel multitaper method

NASA Astrophysics Data System (ADS)

Qi, Pei-Han; Li, Zan; Si, Jiang-Bo; Xiong, Tian-Yi

2015-04-01

Wideband spectrum sensing has drawn much attention in recent years since it provides more opportunities to the secondary users. However, wideband spectrum sensing requires a long time and a complex mechanism at the sensing terminal. A two-stage wideband spectrum sensing scheme is considered to proceed spectrum sensing with low time consumption and high performance to tackle this predicament. In this scheme, a novel multitaper spectrum sensing (MSS) method is proposed to mitigate the poor performance of energy detection (ED) in the low signal-to-noise ratio (SNR) region. The closed-form expression of the decision threshold is derived based on the Neyman-Pearson criterion and the probability of detection in the Rayleigh fading channel is analyzed. An optimization problem is formulated to maximize the probability of detection of the proposed two-stage scheme and the average sensing time of the two-stage scheme is analyzed. Numerical results validate the efficiency of MSS and show that the two-stage spectrum sensing scheme enjoys higher performance in the low SNR region and lower time cost in the high SNR region than the single-stage scheme. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the China Postdoctoral Science Foundation (Grant No. 2014M550479), and the Doctorial Programs Foundation of the Ministry of Education, China (Grant No. 20110203110011).

Double-Difference Global Adjoint Tomography

NASA Astrophysics Data System (ADS)

Orsvuran, R.; Bozdag, E.; Lei, W.; Tromp, J.

2017-12-01

The adjoint method allows us to incorporate full waveform simulations in inverse problems. Misfit functions play an important role in extracting the relevant information from seismic waveforms. In this study, our goal is to apply the Double-Difference (DD) methodology proposed by Yuan et al. (2016) to global adjoint tomography. Dense seismic networks, such as USArray, lead to higher-resolution seismic images underneath continents. However, the imbalanced distribution of stations and sources poses challenges in global ray coverage. We adapt double-difference multitaper measurements to global adjoint tomography. We normalize each DD measurement by its number of pairs, and if a measurement has no pair, as may frequently happen for data recorded at oceanic stations, classical multitaper measurements are used. As a result, the differential measurements and pair-wise weighting strategy help balance uneven global kernel coverage. Our initial experiments with minor- and major-arc surface waves show promising results, revealing more pronounced structure near dense networks while reducing the prominence of paths towards cluster of stations. We have started using this new measurement in global adjoint inversions, addressing azimuthal anisotropy in upper mantle. Meanwhile, we are working on combining the double-difference approach with instantaneous phase measurements to emphasize contributions of scattered waves in global inversions and extending it to body waves. We will present our results and discuss challenges and future directions in the context of global tomographic inversions.

Refining the Early Devonian time scale using Milankovitch cyclicity in Lochkovian-Pragian sediments (Prague Synform, Czech Republic)

NASA Astrophysics Data System (ADS)

Da Silva, A. C.; Hladil, J.; Chadimová, L.; Slavík, L.; Hilgen, F. J.; Bábek, O.; Dekkers, M. J.

2016-12-01

The Early Devonian geological time scale (base of the Devonian at 418.8 ± 2.9 Myr, Becker et al., 2012) suffers from poor age control, with associated large uncertainties between 2.5 and 4.2 Myr on the stage boundaries. Identifying orbital cycles from sedimentary successions can serve as a very powerful chronometer to test and, where appropriate, improve age models. Here, we focus on the Lochkovian and Pragian, the two lowermost Devonian stages. High-resolution magnetic susceptibility (χin - 5 to 10 cm sampling interval) and gamma ray spectrometry (GRS - 25 to 50 cm sampling interval) records were gathered from two main limestone sections, Požár-CS (118 m, spanning the Lochkov and Praha Formations) and Pod Barrandovem (174 m; Praha Formation), both in the Czech Republic. An additional section (Branžovy, 65 m, Praha Formation) was sampled for GRS (every 50 cm). The χin and GRS records are very similar, so χin variations are driven by variations in the samples' paramagnetic clay mineral content, reflecting changes in detrital input. Therefore, climatic variations are very likely captured in our records. Multiple spectral analysis and statistical techniques such as: Continuous Wavelet Transform, Evolutive Harmonic Analysis, Multi-taper method and Average Spectral Misfit, were used in concert to reach an optimal astronomical interpretation. The Požár-CS section shows distinctly varying sediment accumulation rates. The Lochkovian (essentially equivalent to the Lochkov Formation (Fm.)) is interpreted to include a total of nineteen 405 kyr eccentricity cycles, constraining its duration to 7.7 ± 2.8 Myr. The Praha Fm. includes fourteen 405 kyr eccentricity cycles in the three sampled sections, while the Pragian Stage only includes about four 405 kyr eccentricity cycles, thus exhibiting durations of 5.7 ± 0.6 Myr and 1.7 ± 0.7 Myr respectively. Because the Lochkov Fm. contains an interval with very low sediment accumulation rate and because the Praha Fm. was cross-validated in three different sections, the uncertainty in the duration of the Lochkov Fm. and the Lochkovian is larger than that of the Praha Fm. and Pragian. The new floating time scales for the Lochkovian and Pragian stages have an unprecedented precision, with reduction in the uncertainty by a factor of 1.7 for the Lochkovian and of ∼6 for the Pragian. Furthermore, longer orbital modulation cycles are also identified with periodicities of ∼1000 kyr and 2000-2500 kyr.

Measurement of pattern roughness and local size variation using CD-SEM: current status

NASA Astrophysics Data System (ADS)

Fukuda, Hiroshi; Kawasaki, Takahiro; Kawada, Hiroki; Sakai, Kei; Kato, Takashi; Yamaguchi, Satoru; Ikota, Masami; Momonoi, Yoshinori

2018-03-01

Measurement of line edge roughness (LER) is discussed from four aspects: edge detection, PSD prediction, sampling strategy, and noise mitigation, and general guidelines and practical solutions for LER measurement today are introduced. Advanced edge detection algorithms such as wave-matching method are shown effective for robustly detecting edges from low SNR images, while conventional algorithm with weak filtering is still effective in suppressing SEM noise and aliasing. Advanced PSD prediction method such as multi-taper method is effective in suppressing sampling noise within a line edge to analyze, while number of lines is still required for suppressing line to line variation. Two types of SEM noise mitigation methods, "apparent noise floor" subtraction method and LER-noise decomposition using regression analysis are verified to successfully mitigate SEM noise from PSD curves. These results are extended to LCDU measurement to clarify the impact of SEM noise and sampling noise on LCDU.

The stratospheric QBO signal in the NCEP reanalysis, 1958-2001

NASA Astrophysics Data System (ADS)

Ribera, Pedro; Gallego, David; Peña-Ortiz, Cristina; Gimeno, Luis; Garcia-Herrera, Ricardo; Hernandez, Emiliano; Calvo, Natalia

2003-07-01

The spatiotemporal evolution of the zonal wind in the stratosphere is analyzed based on the use of the NCEP reanalysis (1958-2001). MultiTaper Method-Singular Value Decomposition (MTM-SVD), a frequency-domain analysis method, is applied to isolate significant spatially-coherent variability with narrowband oscillatory character. A quasibiennial oscillation is detected as the most intense coherent signal in the stratosphere, the signal being less intense in the lower levels. There is a clear downward propagation of the signal with time at low latitudes, not evident at mid and high latitudes. There are differences in the behavior of the signal over both hemispheres, being much weaker over the SH. In the NH an anomaly in the zonal wind field, in phase with the equatorial signal, is detected at approximately 60°N. Two different areas at subtropical latitudes are detected to be characterized by wind anomalies opposed to that of the equator.

Application of the Augmented Reality in prototyping the educational simulator in sport - the example of judo

NASA Astrophysics Data System (ADS)

Cieślńiski, Wojciech B.; Sobecki, Janusz; Piepiora, Paweł A.; Piepiora, Zbigniew N.; Witkowski, Kazimierz

2016-04-01

The mental training (Galloway, 2011) is one of the measures of the psychological preparation in sport. Especially such as the judo discipline requires the mental training, due to the fact that the judo is a combat sport, the direct, physical confrontation of two opponents. Hence the mental preparation should be an essential element of preparing for the sports fight. In the article are described the basics of the AR systems and presents selected elements of the AR systems: sight glasses Vuzix glasses, Kinect sensor and an interactive floor Multitap. Next, there are proposed the scenarios for using the AR in the mental training which are based on using both Vuzix glasses type head as well as the interactive floor Multitap. All options, except for the last, are provided for using the Kinect sensor. In addition, these variants differ as to the primary user of the system. It can be an competitor, his coach the competitor and the coach at the same time. In the end of the article are presented methods of exploring, both, the effectiveness and usefulness, and/or the User Experience of the proposed prototypes. There are presented three educational training simulator prototype models in sport (judo) describing their functionality based on the theory of sports training (the cyclical nature of sports training) and the theory of subtle interactions, enabling an explanation of the effects of sports training using the augmented reality technology.

A Picea crassifolia Tree-Ring Width-Based Temperature Reconstruction for the Mt. Dongda Region, Northwest China, and Its Relationship to Large-Scale Climate Forcing

PubMed Central

Liu, Yu; Sun, Changfeng; Li, Qiang; Cai, Qiufang

2016-01-01

The historical May–October mean temperature since 1831 was reconstructed based on tree-ring width of Qinghai spruce (Picea crassifolia Kom.) collected on Mt. Dongda, North of the Hexi Corridor in Northwest China. The regression model explained 46.6% of the variance of the instrumentally observed temperature. The cold periods in the reconstruction were 1831–1889, 1894–1901, 1908–1934 and 1950–1952, and the warm periods were 1890–1893, 1902–1907, 1935–1949 and 1953–2011. During the instrumental period (1951–2011), an obvious warming trend appeared in the last twenty years. The reconstruction displayed similar patterns to a temperature reconstruction from the east-central Tibetan Plateau at the inter-decadal timescale, indicating that the temperature reconstruction in this study was a reliable proxy for Northwest China. It was also found that the reconstruction series had good consistency with the Northern Hemisphere temperature at a decadal timescale. Multi-taper method spectral analysis detected some low- and high-frequency cycles (2.3–2.4-year, 2.8-year, 3.4–3.6-year, 5.0-year, 9.9-year and 27.0-year). Combining these cycles, the relationship of the low-frequency change with the Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Southern Oscillation (SO) suggested that the reconstructed temperature variations may be related to large-scale atmospheric-oceanic variations. Major volcanic eruptions were partly reflected in the reconstructed temperatures after high-pass filtering; these events promoted anomalous cooling in this region. The results of this study not only provide new information for assessing the long-term temperature changes in the Hexi Corridor of Northwest China, but also further demonstrate the effects of large-scale atmospheric-oceanic circulation on climate change in Northwest China. PMID:27509206

Accounting for the Effect of Earth's Rotation in Magnetotelluric Inference

NASA Astrophysics Data System (ADS)

Riegert, D. L.; Thomson, D. J.

2017-12-01

The study of geomagnetism has been documented as far back as 1722 when the watchmaker G. Graham constructed a more sensitive compass and showed that the variations in geomagnetic direction varied with an irregular daily pattern. Increased interest in geomagnetism in geomagnetism began at the end of the 19th century (Lamb, Schuster, Chapman, and Price). The Magnetotelluric Method was first introduced in the 1950's (Cagniard and Tikhonov), and, at its core, is simply a regression problem. The result of this method is a transfer function estimate which describes the earth's response to magnetic field variations. This estimate can then be used to infer the earth's subsurface structure; useful for applications such as natural resource exploration. The statistical problem of estimating a transfer function between geomagnetic and induced current measurements has evolved since the 1950's due to a variety of problems: non-stationarity, outliers, and violation of Gaussian assumptions. To address some of these issues, robust regression methods (Chave and Thomson, 2004) and the remote reference method (Gambel, 1979) have been proposed and used. The current method seems to provide reasonable estimates, but still requires a large amount of data. Using the multitaper method of spectral analysis (Thomson, 1982), taking long (greater than 4 months) blocks of geomagnetic data, and concentrating on frequencies below 1000 microhertz to avoid ultraviolet effects, one finds that:1) the cross-spectra are dominated by many offset frequencies including plus and minus 1 and 2 cycles per day;2) the coherence at these offset frequencies is often stronger than at zero offset;3) there are strong couplings from the "quasi two-day" cycle;4) frequencines are usually not symmetric;5) the spectra are dominated by the normal modes of the Sun. This talk will discuss the method of incorporating these observations into the transfer function estimation model, some of the difficulties that arose, their solutions, and current results.

Detecting the Spectrum of the Atlantic's Thermo-haline Circulation: Deconvolved Climate Proxies Show How Polar Climates Communicate

NASA Astrophysics Data System (ADS)

Reischmann, Elizabeth; Yang, Xiao; Rial, José

2014-05-01

Deconvolution is widely used in a wide variety of scientific fields, including its significant use in seismology, as a tool to recover real input from a system's impulse response and output. Our research uses spectral division deconvolution in the context of studying the impulse response of the possible relationship between the nonlinear climates of the Polar Regions by using select δ18O ice cores from both poles. This is feasible in spite of the fact that the records may be the result of nonlinear processes because the two polar climates are synchronized for the period studied, forming a Hilbert transform pair. In order to perform this analysis, the age models of three Greenland and four Antarctica records have been matched using a Monte Carlo method with the methane-matched pair GRIP and BYRD as a basis of calculations. For all of the twelve resulting pairs, various deconvolutions schemes (Weiner, Damped Least Squares, Tikhonov, Truncated Singular Value Decomposition) give consistent, quasi-periodic, impulse responses of the system. Multitaper analysis then demonstrates strong, millennia scale, quasi-periodic oscillations in these system responses with a range of 2,500 to 1,000 years. However, these results are directionally dependent, with the transfer function from north to south differing from that of south north. High amplitude power peaks at 5,000 to 1,7000 years characterize the former, while the latter contains peaks at 2,500 to 1,700 years. These predominant periodicities are also found in the data, some of which have been identified as solar forcing, but others of which may indicate internal oscillations of the climate system (1.6-1.4ky). The approximately 1,500 year period transfer function, which does not have a corresponding solar forcing, may indicate one of these internal periodicities of the system, perhaps even indicating the long-term presence of the Deep Water circulation, also known as the thermo-haline circulation (THC). Simplified models of the polar climate fluctuations are shown to support these findings.

Windowed multitaper correlation analysis of multimodal brain monitoring parameters.

PubMed

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

Spatiotemporal dynamics of rhythmic spinal interneurons measured with two-photon calcium imaging and coherence analysis.

PubMed

Kwan, Alex C; Dietz, Shelby B; Zhong, Guisheng; Harris-Warrick, Ronald M; Webb, Watt W

2010-12-01

In rhythmic neural circuits, a neuron often fires action potentials with a constant phase to the rhythm, a timing relationship that can be functionally significant. To characterize these phase preferences in a large-scale, cell type-specific manner, we adapted multitaper coherence analysis for two-photon calcium imaging. Analysis of simulated data showed that coherence is a simple and robust measure of rhythmicity for calcium imaging data. When applied to the neonatal mouse hindlimb spinal locomotor network, the phase relationships between peak activity of >1,000 ventral spinal interneurons and motor output were characterized. Most interneurons showed rhythmic activity that was coherent and in phase with the ipsilateral motor output during fictive locomotion. The phase distributions of two genetically identified classes of interneurons were distinct from the ensemble population and from each other. There was no obvious spatial clustering of interneurons with similar phase preferences. Together, these results suggest that cell type, not neighboring neuron activity, is a better indicator of an interneuron's response during fictive locomotion. The ability to measure the phase preferences of many neurons with cell type and spatial information should be widely applicable for studying other rhythmic neural circuits.

Atlantic and Pacific Influences on Mesoamerican Climate Over the Past Millennium (Invited)

NASA Astrophysics Data System (ADS)

Stahle, D. W.; Burnette, D. J.; Villanueva, J.; Cleaveland, M. K.

2010-12-01

Montezuma baldcypress (Taxodium mucronatum) trees in Queretaro have been used to develop the first exactly dated millennium-long tree-ring chronology in central Mexico. The chronology is sensitive to both precipitation and temperature, and has been used to reconstruct the Palmer Drought Severity Index (PDSI) for June from AD 771-2008 for a large sector of Mesoamerica (most of central and southern Mexico). Fourier-transform spectral analyses of the 1,238-year long reconstruction indicate strong concentrations of variance at frequencies associated with the El Nino/Southern Oscillation (ENSO; representing over 14% of the total reconstructed variance between periods of 4.5 and 5.5 years), and at multi-decadal frequencies potentially associated with the Atlantic Multidecadal Oscillation (AMO; representing over 10% of the total variance between periods of 50 and 75 years). Weaker but statistically significant concentrations of variance are also detected with the Multi-Taper Method of spectral analysis at subdecadal timescales potentially linked with the North Atlantic Oscillation (NAO; 7.5 years) and at timescales possibly associated with the Pacific Decadal Oscillation (~33 years). The reconstruction is significantly correlated with sea surface temperatures (SST) in the ENSO cold tongue region from 1871-2008 (during the boreal cool season, DJFM), and this SST correlation strengthens in the 20th Century (1931-2008). Summer drought tends to develop over central Mexico during El Nino events, and the record warm events observed in 1983 and 1998 were associated with the two most extremely dry June PDSI conditions in the past 1,238 years (reconstructed ranks 1 and 2 for 1983 and 1998, respectively). The reconstruction is also significantly correlated with SSTs over the tropical North Atlantic, and is coherent with long instrument-based indices of the NAO at periods near 7.5 years, but only during the 20th century. The June PDSI reconstruction is coherent (P<0.05) with a 600-year long tree-ring reconstruction of the NAO at multidecadal timescales (50 to 70-years) during a 200-year episode in the 16th and 17th centuries. The reconstruction indicates more severe and sustained droughts over Mesoamerica before AD 1600, as has been reconstructed previously for western North America. The existence and timing of the Terminal Classic Drought at AD 900 is confirmed with the new reconstruction, which also documents megadroughts during the decline of the Toltec state at Tula and during the rise and fall of the Aztec imperial state in the Valley of Mexico. The long June PDSI reconstruction provides an interesting new paleoclimate framework for the analysis of Mesoamerican climate dynamics and cultural change.

A Robust Deconvolution Method based on Transdimensional Hierarchical Bayesian Inference

NASA Astrophysics Data System (ADS)

Kolb, J.; Lekic, V.

2012-12-01

Analysis of P-S and S-P conversions allows us to map receiver side crustal and lithospheric structure. This analysis often involves deconvolution of the parent wave field from the scattered wave field as a means of suppressing source-side complexity. A variety of deconvolution techniques exist including damped spectral division, Wiener filtering, iterative time-domain deconvolution, and the multitaper method. All of these techniques require estimates of noise characteristics as input parameters. We present a deconvolution method based on transdimensional Hierarchical Bayesian inference in which both noise magnitude and noise correlation are used as parameters in calculating the likelihood probability distribution. Because the noise for P-S and S-P conversion analysis in terms of receiver functions is a combination of both background noise - which is relatively easy to characterize - and signal-generated noise - which is much more difficult to quantify - we treat measurement errors as an known quantity, characterized by a probability density function whose mean and variance are model parameters. This transdimensional Hierarchical Bayesian approach has been successfully used previously in the inversion of receiver functions in terms of shear and compressional wave speeds of an unknown number of layers [1]. In our method we used a Markov chain Monte Carlo (MCMC) algorithm to find the receiver function that best fits the data while accurately assessing the noise parameters. In order to parameterize the receiver function we model the receiver function as an unknown number of Gaussians of unknown amplitude and width. The algorithm takes multiple steps before calculating the acceptance probability of a new model, in order to avoid getting trapped in local misfit minima. Using both observed and synthetic data, we show that the MCMC deconvolution method can accurately obtain a receiver function as well as an estimate of the noise parameters given the parent and daughter components. Furthermore, we demonstrate that this new approach is far less susceptible to generating spurious features even at high noise levels. Finally, the method yields not only the most-likely receiver function, but also quantifies its full uncertainty. [1] Bodin, T., M. Sambridge, H. Tkalčić, P. Arroucau, K. Gallagher, and N. Rawlinson (2012), Transdimensional inversion of receiver functions and surface wave dispersion, J. Geophys. Res., 117, B02301

Adjoint tomography of Europe

NASA Astrophysics Data System (ADS)

Zhu, H.; Bozdag, E.; Peter, D. B.; Tromp, J.

2010-12-01

We use spectral-element and adjoint methods to image crustal and upper mantle heterogeneity in Europe. The study area involves the convergent boundaries of the Eurasian, African and Arabian plates and the divergent boundary between the Eurasian and North American plates, making the tectonic structure of this region complex. Our goal is to iteratively fit observed seismograms and improve crustal and upper mantle images by taking advantage of 3D forward and inverse modeling techniques. We use data from 200 earthquakes with magnitudes between 5 and 6 recorded by 262 stations provided by ORFEUS. Crustal model Crust2.0 combined with mantle model S362ANI comprise the initial 3D model. Before the iterative adjoint inversion, we determine earthquake source parameters in the initial 3D model by using 3D Green functions and their Fréchet derivatives with respect to the source parameters (i.e., centroid moment tensor and location). The updated catalog is used in the subsequent structural inversion. Since we concentrate on upper mantle structures which involve anisotropy, transversely isotropic (frequency-dependent) traveltime sensitivity kernels are used in the iterative inversion. Taking advantage of the adjoint method, we use as many measurements as can obtain based on comparisons between observed and synthetic seismograms. FLEXWIN (Maggi et al., 2009) is used to automatically select measurement windows which are analyzed based on a multitaper technique. The bandpass ranges from 15 second to 150 second. Long-period surface waves and short-period body waves are combined in source relocations and structural inversions. A statistical assessments of traveltime anomalies and logarithmic waveform differences is used to characterize the inverted sources and structure.

Ambient-noise Tomography of the Southern California Lithosphere

NASA Astrophysics Data System (ADS)

Basini, P.; Liu, Q.; Tape, C.

2012-12-01

We exploit the stacked ambient noise cross-correlation functions (NCF) to improve the 3-D velocity structures of southern California crust and upper mantle. NCFs are extracted between pairs of seismic stations as approximations to 3D Greens functions based on the assumption of diffuse wavefields. Thanks to the dense instrumental coverage in south California a high number (around 13000) of NCFs are available that allow us to reach anunprecedented high imaging resolution. The 3-D crustal model m16 of Tape et al. (2009) which describes the detailed crustal variation of southern California region is incorporated into the starting model of our adjoint tomographic inversions. The use of 3D initial model help reduce the nonlinearity of the inverse problem and the number of required iterations. We iteratively improve the velocity model by combining spectral-element (SEM) simulations of seismic wave propagation with Frechet derivatives computed by adjoint methods. The multi-taper traveltime misfit function that quantifies the difference between NCFs (measured over the windows of predominantly surface waves at the period range of 10-20 seconds) and 3D Greens functions for the current model also defines the adjoint sources which produces the necessary Frechet derivatives (sensitivity kernels) through an adjoint simulation. Interesting mantle heterogeneities are revealed due to the improved depth resolution of surface waves. The quality of inversion results may be assessed through the misfit between NCFs and Greens functions for the final model in terms of traveltime, amplitude as well as full waveform. An independent set of earthquakes data and synthetics may also be introduced to verify the final mode.

Adjoint Tomography of the Southern California Crust (Invited) (Invited)

NASA Astrophysics Data System (ADS)

Tape, C.; Liu, Q.; Maggi, A.; Tromp, J.

2009-12-01

We iteratively improve a three-dimensional tomographic model of the southern California crust using numerical simulations of seismic wave propagation based on a spectral-element method (SEM) in combination with an adjoint method. The initial 3D model is provided by the Southern California Earthquake Center. The dataset comprises three-component seismic waveforms (i.e. both body and surface waves), filtered over the period range 2-30 s, from 143 local earthquakes recorded by a network of 203 stations. Time windows for measurements are automatically selected by the FLEXWIN algorithm. The misfit function in the tomographic inversion is based on frequency-dependent multitaper traveltime differences. The gradient of the misfit function and related finite-frequency sensitivity kernels for each earthquake are computed using an adjoint technique. The kernels are combined using a source subspace projection method to compute a model update at each iteration of a gradient-based minimization algorithm. The inversion involved 16 iterations, which required 6800 wavefield simulations and a total of 0.8 million CPU hours. The new crustal model, m16, is described in terms of independent shear (Vs) and bulk-sound (Vb) wavespeed variations. It exhibits strong heterogeneity, including local changes of ±30% with respect to the initial 3D model. The model reveals several features that relate to geologic observations, such as sedimentary basins, exhumed batholiths, and contrasting lithologies across faults. The quality of the new model is validated by quantifying waveform misfits of full-length seismograms from 91 earthquakes that were not used in the tomographic inversion. The new model provides more accurate synthetic seismograms that will benefit seismic hazard assessment.

Linear Array Ambient Noise Adjoint Tomography Reveals Intense Crust-Mantle Interactions in North China Craton

NASA Astrophysics Data System (ADS)

Zhang, Chao; Yao, Huajian; Liu, Qinya; Zhang, Ping; Yuan, Yanhua O.; Feng, Jikun; Fang, Lihua

2018-01-01

We present a 2-D ambient noise adjoint tomography technique for a linear array with a significant reduction in computational cost and show its application to an array in North China. We first convert the observed data for 3-D media, i.e., surface-wave empirical Green's functions (EGFs) to the reconstructed EGFs (REGFs) for 2-D media using a 3-D/2-D transformation scheme. Different from the conventional steps of measuring phase dispersion, this technology refines 2-D shear wave speeds along the profile directly from REGFs. With an initial model based on traditional ambient noise tomography, adjoint tomography updates the model by minimizing the frequency-dependent Rayleigh wave traveltime delays between the REGFs and synthetic Green functions calculated by the spectral-element method. The multitaper traveltime difference measurement is applied in four-period bands: 20-35 s, 15-30 s, 10-20 s, and 6-15 s. The recovered model shows detailed crustal structures including pronounced low-velocity anomalies in the lower crust and a gradual crust-mantle transition zone beneath the northern Trans-North China Orogen, which suggest the possible intense thermo-chemical interactions between mantle-derived upwelling melts and the lower crust, probably associated with the magmatic underplating during the Mesozoic to Cenozoic evolution of this region. To our knowledge, it is the first time that ambient noise adjoint tomography is implemented for a 2-D medium. Compared with the intensive computational cost and storage requirement of 3-D adjoint tomography, this method offers a computationally efficient and inexpensive alternative to imaging fine-scale crustal structures beneath linear arrays.

Windowed Multitaper Correlation Analysis of Multimodal Brain Monitoring Parameters

PubMed Central

Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome. PMID:25821507

Tunable radio-frequency photonic filter based on an actively mode-locked fiber laser.

PubMed

Ortigosa-Blanch, A; Mora, J; Capmany, J; Ortega, B; Pastor, D

2006-03-15

We propose the use of an actively mode-locked fiber laser as a multitap optical source for a microwave photonic filter. The fiber laser provides multiple optical taps with an optical frequency separation equal to the external driving radio-frequency signal of the laser that governs its repetition rate. All the optical taps show equal polarization and an overall Gaussian apodization, which reduces the sidelobes. We demonstrate continuous tunability of the filter by changing the external driving radio-frequency signal of the laser, which shows good fine tunability in the operating range of the laser from 5 to 10 GHz.

Detection of the secondary meridional circulation associated with the quasi-biennial oscillation

NASA Astrophysics Data System (ADS)

Ribera, P.; PeñA-Ortiz, C.; Garcia-Herrera, R.; Gallego, D.; Gimeno, L.; HernáNdez, E.

2004-09-01

The quasi-biennial oscillation (QBO) signal in stratospheric zonal and meridional wind, temperature, and geopotential height fields is analyzed based on the use of the National Centers for Environmental Prediction (NCEP) reanalysis (1958-2001). The multitaper method-singular value decomposition (MTM-SVD), a multivariate frequency domain analysis method, is used to detect significant and spatially coherent narrowband oscillations. The QBO is found as the most intense signal in the stratospheric zonal wind. Then, the MTM-SVD method is used to determine the patterns induced by the QBO at every stratospheric level and data field. The secondary meridional circulation associated with the QBO is identified in the obtained patterns. This circulation can be characterized by negative (positive) temperature anomalies associated with adiabatic rising (sinking) motions over zones of easterly (westerly) wind shear and over the subtropics and midlatitudes, while meridional convergence and divergence levels are found separated by a level of maximum zonal wind shear. These vertical and meridional motions form quasi-symmetric circulation cells over both hemispheres, though less intense in the Southern Hemisphere.

Resting-state EEG study of comatose patients: a connectivity and frequency analysis to find differences between vegetative and minimally conscious states

PubMed Central

Lehembre, Rémy; Bruno, Marie-Aurélie; Vanhaudenhuyse, Audrey; Chatelle, Camille; Cologan, Victor; Leclercq, Yves; Soddu, Andrea; Macq, Benoît; Laureys, Steven; Noirhomme, Quentin

2012-01-01

Summary The aim of this study was to look for differences in the power spectra and in EEG connectivity measures between patients in the vegetative state (VS/UWS) and patients in the minimally conscious state (MCS). The EEG of 31 patients was recorded and analyzed. Power spectra were obtained using modern multitaper methods. Three connectivity measures (coherence, the imaginary part of coherency and the phase lag index) were computed. Of the 31 patients, 21 were diagnosed as MCS and 10 as VS/UWS using the Coma Recovery Scale-Revised (CRS-R). EEG power spectra revealed differences between the two conditions. The VS/UWS patients showed increased delta power but decreased alpha power compared with the MCS patients. Connectivity measures were correlated with the CRS-R diagnosis; patients in the VS/UWS had significantly lower connectivity than MCS patients in the theta and alpha bands. Standard EEG recorded in clinical conditions could be used as a tool to help the clinician in the diagnosis of disorders of consciousness. PMID:22687166

ConceFT for Time-Varying Heart Rate Variability Analysis as a Measure of Noxious Stimulation During General Anesthesia.

PubMed

Lin, Yu-Ting; Wu, Hau-Tieng

2017-01-01

Heart rate variability (HRV) offers a noninvasive way to peek into the physiological status of the human body. When this physiological status is dynamic, traditional HRV indices calculated from power spectrum do not resolve the dynamic situation due to the issue of nonstationarity. Clinical anesthesia is a typically dynamic situation that calls for time-varying HRV analysis. Concentration of frequency and time (ConceFT) is a nonlinear time-frequency (TF) analysis generalizing the multitaper technique and the synchrosqueezing transform. The result is a sharp TF representation capturing the dynamics inside HRV. Companion indices of the commonly applied HRV indices, including time-varying low-frequency power (tvLF), time-varying high-frequency power, and time-varying low-high ratio, are considered as measures of noxious stimulation. To evaluate the feasibility of the proposed indices, we apply these indices to study two different types of noxious stimulation, the endotracheal intubation and surgical skin incision, under general anesthesia. The performance was compared with traditional HRV indices, the heart rate reading, and indices from electroencephalography. The results indicate that the tvLF index performs best and outperforms not only the traditional HRV index, but also the commonly used heart rate reading. With the help of ConceFT, the proposed HRV indices are potential to provide a better quantification of the dynamic change of the autonomic nerve system. Our proposed scheme of time-varying HRV analysis could contribute to the clinical assessment of analgesia under general anesthesia.

Effective elastic thickness along the conjugate passive margins of India, Madagascar and Antarctica: A re-evaluation using the Hermite multitaper Bouguer coherence application

NASA Astrophysics Data System (ADS)

Ratheesh-Kumar, R. T.; Xiao, Wenjiao

2018-05-01

Gondwana correlation studies had rationally positioned the western continental margin of India (WCMI) against the eastern continental margin of Madagascar (ECMM), and the eastern continental margin of India (ECMI) against the eastern Antarctica continental margin (EACM). This contribution computes the effective elastic thickness (Te) of the lithospheres of these once-conjugated continental margins using the multitaper Bouguer coherence method. The results reveal significantly low strength values (Te ∼ 2 km) in the central segment of the WCMI that correlate with consistently low Te values (2-3 km) obtained throughout the entire marginal length of the ECMM. This result is consistent with the previous Te estimates of these margins, and confirms the idea that the low-Te segments in the central part of the WCMI and along the ECMM represents paleo-rift inception points of the lithospheric margins that was thermally and mechanically weakened by the combined action of the Marion hotspot and lithospheric extension during the rifting. The uniformly low-Te value (∼2 km) along the EACM indicates a mechanically weak lithospheric margin, probably due to considerable stretching of the lithosphere, considering the fact that this margin remained almost stationary throughout its rift history. In contrast, the ECMI has comparatively high-Te variations (5-11 km) that lack any correlation with the regional tectonic setting. Using gravity forward and inversion applications, we find a leading order of influence of sediment load on the flexural properties of this marginal lithosphere. The study concludes that the thick pile of the Bengal Fan sediments in the ECMI masks and has erased the signal of the original load-induced topography, and its gravity effect has biased the long-wavelength part of the observed gravity signal. The hence uncorrelated flat topography and deep lithospheric flexure together contribute a bias in the flexure modeling, which likely accounts a relatively high Te estimate.

SEISMIC SOURCE SCALING AND DISCRIMINATION IN DIVERSE TECTONIC ENVIRONMENTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abercrombie, R E; Mayeda, K; Walter, W R

2008-07-08

The objectives of this study are to improve low-magnitude (concentrating on M2.5-5) regional seismic discrimination by performing a thorough investigation of earthquake source scaling using diverse, high-quality datasets from varied tectonic regions. Local-to-regional high-frequency discrimination requires an estimate of how earthquakes scale with size. Walter and Taylor (2002) developed the MDAC (Magnitude and Distance Amplitude Corrections) method to empirically account for these effects through regional calibration. The accuracy of these corrections has a direct impact on our ability to identify clandestine explosions in the broad regional areas characterized by low seismicity. Unfortunately our knowledge at small magnitudes (i.e., m{sub b}more » < {approx} 4.0) is poorly resolved, and source scaling remains a subject of on-going debate in the earthquake seismology community. Recently there have been a number of empirical studies suggesting scaling of micro-earthquakes is non-self-similar, yet there are an equal number of compelling studies that would suggest otherwise. It is not clear whether different studies obtain different results because they analyze different earthquakes, or because they use different methods. Even in regions that are well studied, such as test sites or areas of high seismicity, we still rely on empirical scaling relations derived from studies taken from half-way around the world at inter-plate regions. We investigate earthquake sources and scaling from different tectonic settings, comparing direct and coda wave analysis methods that both make use of empirical Green's function (EGF) earthquakes to remove path effects. Analysis of locally recorded, direct waves from events is intuitively the simplest way of obtaining accurate source parameters, as these waves have been least affected by travel through the earth. But finding well recorded earthquakes with 'perfect' EGF events for direct wave analysis is difficult, limits the number of earthquakes that can be studied. We begin with closely-located, well-correlated earthquakes. We use a multi-taper method to obtain time-domain source-time-functions by frequency division. We only accept an earthquake and EGF pair if they are able to produce a clear, time-domain source pulse. We fit the spectral ratios and perform a grid-search about the preferred parameters to ensure the fits are well constrained. We then model the spectral (amplitude) ratio to determine source parameters from both direct P and S waves. We analyze three clusters of aftershocks from the well-recorded sequence following the M5 Au Sable Forks, NY, earthquake to obtain some of the first accurate source parameters for small earthquakes in eastern North America. Each cluster contains a M{approx}2, and two contain M{approx}3, as well as smaller aftershocks. We find that the corner frequencies and stress drops are high (averaging 100 MPa) confirming previous work suggesting that intraplate continental earthquakes have higher stress drops than events at plate boundaries. We also demonstrate that a scaling breakdown suggested by earlier work is simply an artifact of their more band-limited data. We calculate radiated energy, and find that the ratio of Energy to seismic Moment is also high, around 10{sup -4}. We estimate source parameters for the M5 mainshock using similar methods, but our results are more doubtful because we do not have a EGF event that meets our preferred criteria. The stress drop and energy/moment ratio for the mainshock are slightly higher than for the aftershocks. Our improved, and simplified coda wave analysis method uses spectral ratios (as for the direct waves) but relies on the averaging nature of the coda waves to use EGF events that do not meet the strict criteria of similarity required for the direct wave analysis. We have applied the coda wave spectral ratio method to the 1999 Hector Mine mainshock (M{sub w} 7.0, Mojave Desert) and its larger aftershocks, and also to several sequences in Italy with M{approx}6 mainshocks. The Italian earthquakes have higher stress drops than the Hector Mine sequence, but lower than Au Sable Forks. These results show a departure from self-similarity, consistent with previous studies using similar regional datasets. The larger earthquakes have higher stress drops and energy/moment ratios. We perform a preliminary comparison of the two methods using the M5 Au Sable Forks earthquake. Both methods give very consistent results, and we are applying the comparison to further events.« less

Spatial correlations of interdecadal variation in global surface temperatures

NASA Technical Reports Server (NTRS)

Mann, Michael E.; Park, Jeffrey

1993-01-01

We have analyzed spatial correlation patterns of interdecadal global surface temperature variability from an empirical perspective. Using multitaper coherence estimates from 140-yr records, we find that correlations between hemispheres are significant at about 95 percent confidence for nonrandomness for most of the frequency band in the 0.06-0.24 cyc/yr range. Coherence estimates of pairs of 100-yr grid-point temperature data series near 5-yr period reveal teleconnection patterns consistent with known patterns of ENSO variability. Significant correlated variability is observed near 15 year period, with the dominant teleconnection pattern largely confined to the Northern Hemisphere. Peak-to-peak Delta-T is at about 0.5 deg, with simultaneous warming and cooling of discrete patches on the earth's surface. A global average of this pattern would largely cancel.

Synthetic Foveal Imaging Technology

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Monacos, Steve P. (Inventor); Hoenk, Michael E. (Inventor)

2013-01-01

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

Magnetic Orbital and Reversal Stratigraphy of the Johnnie Formation, Death Valley region, with implications for the Shuram Carbon Isotope Excursion

NASA Astrophysics Data System (ADS)

Minguez, D. A.; Kodama, K. P.; Hillhouse, J. W.

2012-12-01

This study demonstrates a ~720 kyr depositional period for 33 meters of dolomites from the Johnnie Formation at the Winters Pass Hills locality in Death Valley, CA. These dolomites have been shown to record the Shuram carbon isotope anomaly (Corsetti and Kaufman, 2003). We provide a new record of the anomaly that demonstrates the presence of the Shuram excursion from its nadir of δ13C= -12 ‰ to a recovered value of -8 ‰. By comparison to a full stratigraphic reconstruction of the Shuram Excursion by Verdel et al. (2011) the measured section from this study represents roughly 1/10 of the Shuram excursion, suggesting a 7.2 myr duration for the complete excursion, significantly shorter than the 50 myr estimate of Le Guerroué et al. (2006). The orbitally-forced stratigraphy used to make this measurement was obtained by performing multi-taper method spectral analysis on data series of magnetic susceptibility and a magnetically measured goethite to hematite ratio. Cyclic variations in magnetic susceptibility with wavelengths of 18.6 m and 5.4 m are observed in the spectrum above the 95% significance level with respect to the robust red noise and are interpreted to represent varying concentrations of paramagnetic clay particles forced by climate controlled weathering and transport of sediment to the ancient Laurentian passive margin. 0.63m and 0.71 m wavelength cycles with spectral peaks above the 95% significance level are also observed. A magnetic reversal stratigraphy developed by thermal demagnetization of oriented samples demonstrates three polarity intervals in the dolomites of the Winters Pass Hills, constraining the depositional period of the dolomites to <1 myr (estimate of magnetic reversal frequency for the Meso-NeoProterozoic based on Pavlov and Gallet, 2010). This suggests that cycles with wavelengths of 18.6m, 5.4m, and 0.71m represent long eccentricity, short eccentricity, and precession, respectively. The ratio of goethite to hematite also varies cyclically with wavelengths of 18.6m, 5.8m, and 0.63m. The goethite is most likely the product of present day weathering and may represent variations in depositional Fe-rich clay particles. These results replicate results obtained by Kodama and Hillhouse (2011) in the Nopah Range of Death Valley, approximately 40 km to the north. The Nopah Range rocks were deposited in a more distal sedimentary environment in the same depositional basin. The agreement between the two studies suggests a basin wide response to climatic forcing of depositional processes observable by the rock magnetic cyclostratigraphy. Assuming the period of Earth's long eccentricity has not varied significantly since the Ediacaran period (Laskar et al., 2011; Berger and Loutre, 1994) and that the magnetostratigraphy constrains the 33 m section to <1 myr, depositional cycles of 18.6m represent ~400 kyr, 5.4 m cycles represent ~116 kyr, and 0.71m cycles represent ~15 kyr.

The Atacama Cosmology Telescope: A Measurement of the 600 less than l less than 8000 Cosmic Microwave Background Power Spectrum at 148 GHz

NASA Technical Reports Server (NTRS)

Fowler, J. W.; Acquaviva, V.; Ade, P. A. R.; Aguirre, P.; Amiri, M.; Appel, J. W.; Barrientos, L. F.; Bassistelli, E. S.; Bond, J. R.; Brown, B.;

Spectral mapping tools from the earth sciences applied to spectral microscopy data.

PubMed

Harris, A Thomas

2006-08-01

Spectral imaging, originating from the field of earth remote sensing, is a powerful tool that is being increasingly used in a wide variety of applications for material identification. Several workers have used techniques like linear spectral unmixing (LSU) to discriminate materials in images derived from spectral microscopy. However, many spectral analysis algorithms rely on assumptions that are often violated in microscopy applications. This study explores algorithms originally developed as improvements on early earth imaging techniques that can be easily translated for use with spectral microscopy. To best demonstrate the application of earth remote sensing spectral analysis tools to spectral microscopy data, earth imaging software was used to analyze data acquired with a Leica confocal microscope with mechanical spectral scanning. For this study, spectral training signatures (often referred to as endmembers) were selected with the ENVI (ITT Visual Information Solutions, Boulder, CO) "spectral hourglass" processing flow, a series of tools that use the spectrally over-determined nature of hyperspectral data to find the most spectrally pure (or spectrally unique) pixels within the data set. This set of endmember signatures was then used in the full range of mapping algorithms available in ENVI to determine locations, and in some cases subpixel abundances of endmembers. Mapping and abundance images showed a broad agreement between the spectral analysis algorithms, supported through visual assessment of output classification images and through statistical analysis of the distribution of pixels within each endmember class. The powerful spectral analysis algorithms available in COTS software, the result of decades of research in earth imaging, are easily translated to new sources of spectral data. Although the scale between earth imagery and spectral microscopy is radically different, the problem is the same: mapping material locations and abundances based on unique spectral signatures. (c) 2006 International Society for Analytical Cytology.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2002-01-01

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Enhanced low-temperature performance of a multicell LiSOC1sub2 battery

NASA Astrophysics Data System (ADS)

Street, H. K.

A battery pack with a long life, low current, multitap power supply utilizing lithium thionyl chloride cells (LTC) is described. The battery was developed to provide power to a portable solid state recording accelerometer. The battery pack utilizes 10 Li/SOC12 type LTC-7PN keeper 2 cells. These cells are wired in a series parallel arrangement to provide two 6 volt outputs and two negative 3 volt outputs with a single common. Four 301 K ohm resistors are internally mounted and wired to permit an optional continuous 12 microampere current drain from the cells to eliminate voltage delay effects at very low temperatures. The prewired assembly is encapsulated, using Stepen Foam H-102N rigid polyurethane 2 lbs/ft(3) foam, molded to a density of 4 lbs/ft(3).

Astrochronology of the Valanginian Stage (Early Cretaceous) : implications for the origin of the Weissert Event

NASA Astrophysics Data System (ADS)

Martinez, Mathieu; Deconinck, Jean-François; Pellenard, Pierre; Reboulet, Stéphane; Riquier, Laurent

2013-04-01

Due to the scarcity of available radioisotopic ages in the Lower Cretaceous, the Geologic Time Scale presents uncertainties that impact palaeoceanographic and palaeoclimatic reconstructions. Particularly, the chronological relationship between the Mid-Valanginian carbon-isotope excursion (namely the 'Weissert Event') and the activity of the Paraná-Etendeka Large Igneous Province is debated. To better constrain this relationship, an astrochronology of the Valanginian Stage is proposed based on high-resolution gamma-ray spectrometry measurements performed on five biostratigraphically well-constrained sections throughout the Vocontian Basin (SE France). The Valanginian sediments of the Vocontian Basin are composed of decimetric hemipelagic marl-limestone alternations. These lithologic cycles are attributed to orbital forcing because marls and limestones display significant differences within clay mineralogy, geochemistry and faunal assemblages and these marl-limestone alternations are correlated throughout the Western Tethys and the Atlantic Ocean. Among the analyzed sections, Vergol (GSSP candidate for the Berriasian-Valanginian boundary), La Charce (GSSP candidate for the Valanginian-Hauterivian boundary) and Angles (Valanginian Hypostratotype) are standard sections for the Valanginian Stage since all ammonite zones and subzones are precisely identified and bounded. Spectral analyses were performed using the multi-taper method and amplitude spectrograms on the gamma-ray signals. The comparison between sedimentary frequency ratios derived from the spectral analyses and orbital frequency ratios calculated from astronomical solutions allows the identification of a pervasive dominance of the precession and the 405 kyr-eccentricity cycles throughout the Valanginian Stage. A duration of 5.1 myr is proposed for the Valanginian Stage on the base of the recognition of the 405 kyr-eccentricity cycles. This duration is in agreement with the orbital calibration proposed from δ13C measurements in the Maiolica Formation (Central Italy). By anchoring this proposed astrochronology with available radioisotopic ages for the Berriasian-Hauterivian interval, it appears that the Paraná-Etendeka activity started ~2 myr after the onset of the Weissert Event and therefore can not have induced the carbon-isotope excursion. Instead, following Westermann et al. (2010), we propose that continental carbon organic storage accompanied by carbonate-platform drownings are responsible for the first major carbon-isotope shift of the Cretaceous. Bibliography : Westermann, S., Föllmi, K.B., Adatte, T., Matera, V., Schnyder, J., Fleitmann, D., Fiet, N., Ploch, I., Duchamp-Alphonse, S., 2010. The Valanginian δ13C excrusion may no be an expression of a global oceanic anoxic event. EPSL 290, 118-131.

Anisotropic structure of the mantle wedge beneath the Ryukyu arc from teleseismic receiver function analysis

NASA Astrophysics Data System (ADS)

McCormack, K. A.; Wirth, E. A.; Long, M. D.

2011-12-01

The recycling of oceanic plates back into the mantle through subduction is an important process taking place within our planet. However, many fundamental aspects of subduction systems, such as the dynamics of mantle flow, have yet to be completely understood. Subducting slabs transport water down into the mantle, but how and where that water is released, as well as how it affects mantle flow, is still an open question. In this study, we focus on the Ryukyu subduction zone in southwestern Japan and use anisotropic receiver function analysis to characterize the structure of the mantle wedge. We compute radial and transverse P-to-S receiver functions for eight stations of the broadband F-net array using a multitaper receiver function estimator. We observe coherent P-to-SV converted energy in the radial receiver functions at ~6 sec for most of the stations analyzed consistent with conversions originating at the top of the slab. We also observe conversions on the transverse receiver functions that are consistent with the presence of multiple anisotropic and/or dipping layers. The character of the transverse receiver functions varies significantly along strike, with the northernmost three stations exhibiting markedly different behavior than stations located in the center of the Ryukyu arc. We compute synthetic receiver functions using a forward modeling scheme that can handle dipping interfaces and anisotropic layers to create models for the depths, thicknesses, and strengths of anisotropic layers in the mantle wedge beneath Ryukyu.

Evidence for magmatic underplating and partial melt beneath the Canary Islands derived using teleseismic receiver functions

NASA Astrophysics Data System (ADS)

Lodge, A.; Nippress, S. E. J.; Rietbrock, A.; García-Yeguas, A.; Ibáñez, J. M.

2012-12-01

In recent years, an increasing number of studies have focussed on resolving the internal structure of ocean island volcanoes. Traditionally, active source seismic experiments have been used to image the volcano edifice. Here we present results using the analysis of compressional to shear (P to S) converted seismic phases from teleseismic events, recorded by stations involved in an active source experiment "TOM-TEIDEVS" (Ibáñez et al., 2008), on the island of Tenerife, Canary Islands. We supplement this data with receiver function (RF) analysis of seismograms from the Canary Islands of Lanzarote and La Palma, applying the extended-time multitaper frequency domain cross-correlation estimation method (Helffrich, 2006). We use the neighbourhood inversion approach of Sambridge (1999a,b) to model the RFs and our results indicate magmatic underplating exists beneath all three islands, ranging from 2 to 8 km, but showing no clear correlation with the age of the island. Beneath both La Palma and Tenerife, we find localized low velocity zones (LVZs), which we interpret as due to partial melt, supported by their correlation with the location of historical earthquakes (La Palma) and recent earthquakes (Tenerife). For Lanzarote, we do not sample the most recently volcanically active region and find no evidence for a LVZ. Instead, we find a simple gradational velocity structure, with discontinuities at ˜4, 10 and 18 km depth, in line with previous studies.

Apparatus and system for multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2003-06-24

An apparatus and system for determining the properties of a sample from measured spectral data collected from the sample by performing a method of multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used by a spectrum analyzer to process X-ray spectral data generated by a spectral analysis system that can include a Scanning Electron Microscope (SEM) with an Energy Dispersive Detector and Pulse Height Analyzer.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2004-03-23

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following prediction or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The hybrid method herein means a combination of an initial calibration step with subsequent analysis by an inverse multivariate analysis method. A spectral shape herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The shape can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Analysis of spectrally resolved autofluorescence images by support vector machines

NASA Astrophysics Data System (ADS)

Mateasik, A.; Chorvat, D.; Chorvatova, A.

2013-02-01

Spectral analysis of the autofluorescence images of isolated cardiac cells was performed to evaluate and to classify the metabolic state of the cells in respect to the responses to metabolic modulators. The classification was done using machine learning approach based on support vector machine with the set of the automatically calculated features from recorded spectral profile of spectral autofluorescence images. This classification method was compared with the classical approach where the individual spectral components contributing to cell autofluorescence were estimated by spectral analysis, namely by blind source separation using non-negative matrix factorization. Comparison of both methods showed that machine learning can effectively classify the spectrally resolved autofluorescence images without the need of detailed knowledge about the sources of autofluorescence and their spectral properties.

Quantitative subpixel spectral detection of targets in multispectral images. [terrestrial and planetary surfaces

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Adams, John B.; Smith, Milton O.

1992-01-01

The conditions that affect the spectral detection of target materials at the subpixel scale are examined. Two levels of spectral mixture analysis for determining threshold detection limits of target materials in a spectral mixture are presented, the cases where the target is detected as: (1) a component of a spectral mixture (continuum threshold analysis) and (2) residuals (residual threshold analysis). The results of these two analyses are compared under various measurement conditions. The examples illustrate the general approach that can be used for evaluating the spectral detectability of terrestrial and planetary targets at the subpixel scale.

Imprint of the Atlantic Multidecadal Oscillation on Tree-Ring Widths in Northeastern Asia since 1568

PubMed Central

Wang, Xiaochun; Brown, Peter M.; Zhang, Yanni; Song, Laiping

2011-01-01

We present a new tree-ring reconstruction of the Atlantic Multidecadal Oscillation (AMO) spanning 1568–2007 CE from northeast Asia. Comparison of the instrumental AMO index, an existing tree-ring based AMO reconstruction, and this new record show strongly similar annual to multidecadal patterns of variation over the last 440 years. Warm phases of the AMO are related to increases in growth of Scots pine trees and moisture availability in northeast China and central eastern Siberia. Multi-tape method (MTM) and cross-wavelet analyses indicate that robust multidecadal (∼64–128 years) variability is present throughout the new proxy record. Our results have important implications concerning the influence of North Atlantic sea surface temperatures on East Asian climate, and provide support for the possibility of an AMO signature on global multidecadal climate variability. PMID:21818380

Possibility of successive SRXFA use along with chemical-spectral methods for palladium analysis in geological samples

NASA Astrophysics Data System (ADS)

Kislov, E. V.; Kulikov, A. A.; Kulikova, A. B.

1989-10-01

Samples of basit-ultrabasit rocks and NiCu ores of the Ioko-Dovyren and Chaya massifs were analysed by SRXFA and a chemical-spectral method. SRXFA perfectly satisfies the quantitative noble-metals analysis of ore-free rocks. Combination of SRXFA and chemical-spectral analysis has good prospects. After analysis of a great number of samples by SRXFA it is necessary to select samples which would show minimal and maximal results for the chemical-spectral method.

Characterising volcanic cycles at Soufriere Hills Volcano, Montserrat: Time series analysis of multi-parameter satellite data

NASA Astrophysics Data System (ADS)

Flower, Verity J. B.; Carn, Simon A.

2015-10-01

The identification of cyclic volcanic activity can elucidate underlying eruption dynamics and aid volcanic hazard mitigation. Whilst satellite datasets are often analysed individually, here we exploit the multi-platform NASA A-Train satellite constellation to cross-correlate cyclical signals identified using complementary measurement techniques at Soufriere Hills Volcano (SHV), Montserrat. In this paper we present a Multi-taper (MTM) Fast Fourier Transform (FFT) analysis of coincident SO2 and thermal infrared (TIR) satellite measurements at SHV facilitating the identification of cyclical volcanic behaviour. These measurements were collected by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) (respectively) in the A-Train. We identify a correlating cycle in both the OMI and MODIS data (54-58 days), with this multi-week feature attributable to episodes of dome growth. The 50 day cycles were also identified in ground-based SO2 data at SHV, confirming the validity of our analysis and further corroborating the presence of this cycle at the volcano. In addition a 12 day cycle was identified in the OMI data, previously attributed to variable lava effusion rates on shorter timescales. OMI data also display a one week (7-8 days) cycle attributable to cyclical variations in viewing angle resulting from the orbital characteristics of the Aura satellite. Longer period cycles possibly relating to magma intrusion were identified in the OMI record (102-, 121-, and 159 days); in addition to a 238-day cycle identified in the MODIS data corresponding to periodic destabilisation of the lava dome. Through the analysis of reconstructions generated from cycles identified in the OMI and MODIS data, periods of unrest were identified, including the major dome collapse of 20th May 2006 and significant explosive event of 3rd January 2009. Our analysis confirms the potential for identification of cyclical volcanic activity through combined analysis of satellite data, which would be of particular value at poorly monitored volcanic systems.

Spectral Properties and Dynamics of Gold Nanorods Revealed by EMCCD Based Spectral-Phasor Method

PubMed Central

Chen, Hongtao; Digman, Michelle A.

2015-01-01

Gold nanorods (NRs) with tunable plasmon-resonant absorption in the near-infrared region have considerable advantages over organic fluorophores as imaging agents. However, the luminescence spectral properties of NRs have not been fully explored at the single particle level in bulk due to lack of proper analytic tools. Here we present a global spectral phasor analysis method which allows investigations of NRs' spectra at single particle level with their statistic behavior and spatial information during imaging. The wide phasor distribution obtained by the spectral phasor analysis indicates spectra of NRs are different from particle to particle. NRs with different spectra can be identified graphically in corresponding spatial images with high spectral resolution. Furthermore, spectral behaviors of NRs under different imaging conditions, e.g. different excitation powers and wavelengths, were carefully examined by our laser-scanning multiphoton microscope with spectral imaging capability. Our results prove that the spectral phasor method is an easy and efficient tool in hyper-spectral imaging analysis to unravel subtle changes of the emission spectrum. Moreover, we applied this method to study the spectral dynamics of NRs during direct optical trapping and by optothermal trapping. Interestingly, spectral shifts were observed in both trapping phenomena. PMID:25684346

Observational evidence of planetary wave influences on ozone enhancements over upper troposphere North Africa

NASA Astrophysics Data System (ADS)

Mengistu Tsidu, Gizaw; Ture, Kassahun; Sivakumar, V.

2013-07-01

MOZAIC instrument measured enhanced ozone on two occasions in February, 1996 and 1997 at cruise altitude over North Africa. The cause and source of ozone enhancements over the region are investigated using additional reanalysis data from ERA-Interim. The ERA-Interim reprocessed GOME ozone indicated existence of enhancement as well. Both observational data revealed that the increase in ozone has wider latitudinal coverage extending from North Europe upto North Africa. The geopotential heights and zonal wind from ERA-Interim have indicated existence of planetary-scale flow that allowed meridional airmass exchanges between subtropics and higher latitudes. The presence of troughs-ridge pattern are attributable to large amplitude waves of zonal wavenumber 1-5 propagating eastward in the winter hemisphere westerly current as determined from Hayashi spectra as well as local fractional variance spectra determined from Multitaper Method-Singular Value Decomposition (MTM-SVD) spectral method. MTM-SVD is also used to understand the role of these waves on ozone enhancement and variability during the observation period in a mechanistic approach. A joint analysis of driving field, such as wind and potential vorticity (PV) for which only signals of the dominant zonal wavenumbers of prevailing planetary waves are retained, has revealed strong linkage between wave activity and ozone enhancement over the region at a temporal cycle of 5.8 days. One of these features is the displacement of the polar vortex southward during the enhancements, allowing strong airmass, energy and momentum exchanges. Evidence of cutoff laws that are formed within the deep trough, characteristics of Rossby wave breaking, is also seen in the ozone horizontal distribution at different pressure levels during the events. The reconstruction of signals with the cycle of 5.8 days has shown that the time and strength of enhancement depend on the circulation patterns dictated by planetary-scale flow relative to the location of observation. The positive PV anomalies upstream or at the observation region bring ozone rich airmass to the region while a negative PV anomaly upstream does the opposite. The position of the anomalies with time changes in accordance with the period of the waves involved. The snap shot of coherent variation of PV and ozone at different time during half cycle of the 5.8-day period has indicated that a region could experience positive (enhancement) or negative (depletion) ozone anomalies of different degree as the wave propagates eastward.

Astrochronology of the Pliensbachian-Toarcian transition in the Foum Tillicht section (central High Atlas, Morroco)

NASA Astrophysics Data System (ADS)

Martinez, Mathieu; Bodin, Stéphane; Krencker, François-Nicolas

2015-04-01

The Pliensbachian and Toarcian stages (Early Jurassic) are marked by a series of carbon cycle disturbances, major climatic changes and severe faunal turnovers. An accurate knowledge of the timing of the Pliensbachian-Toarcian age is a key for quantifying fluxes and rhythms of faunal and geochemical processes during these major environmental perturbations. Although many studies provided astrochronological frameworks of the Toarcian Stage and the Toarcian oceanic anoxic event, no precise time frame exists for the Pliensbachian-Toarcian transition, often condensed in the previously studied sections. Here, we provide an astrochronology of the Pliensbachian-Toarcian transition in the Foum Tillicht section (central High Atlas, Morocco). The section is composed of decimetric hemipelagic marl-limestone alternations accompanied by cyclic fluctuations in the δ13Cmicrite. In this section, the marl-limestone alternations reflect cyclic sea-level/climatic changes, which triggers rhythmic migrations of the surrounding carbonate platforms and modulates the amount of carbonate exported to the basin. The studied interval encompasses 142.15 m of the section, from the base of the series to a hiatus in the Early Toarcian, marked by an erosional surface. The Pliensbachian-Toarcian (P-To) Event, a negative excursion in carbonate δ13Cmicrite, is observed pro parte in this studied interval. δ13Cmicrite measurements were performed every ~2 m at the base of the section and every 0.20 m within the P-To Event interval. Spectral analyses were performed using the multi-taper method and the evolutive Fast Fourier Transform to get the accurate assessment of the main significant periods and their evolution throughout the studied interval. Two main cycles are observed in the series: the 405-kyr eccentricity cycles is observed throughout the series, while the obliquity cycles is observed within the P-To Event, in the most densely sampled interval. The studied interval covers a 3.6-Myr interval. The duration of the part of P-To Event covered in this analysis is assessed at 0.70 Myr. In addition, the interval from the base of the Toarcian to the first occurrence of the calcareous nannofossil C. superbus has a duration assessed from 0.47 to 0.55 Myr. This duration is significantly higher than most of assessments obtained by former cyclostratigraphy analyses, showing that previous studies underestimated the duration of this interval, often condensed in the Western Tethys. This study shows the potential of the Foum Tillicht section to provide a refined time frame of the Pliensbachian-Toarcian boundary, which could be integrated in the next Geological Time Scale.

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R.

2007-10-16

A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

The Lithospheric Structure Beneath Canary Islands from Receiver Function Analysis

NASA Astrophysics Data System (ADS)

Martinez-Arevalo, C.; Mancilla, F.; Helffrich, G. R.; Garcia, A.

2009-12-01

The Canary Archipelago is located a few hundred kilometers off the western Moroccan coast, extending 450 km west-to-east. It is composed of seven main islands. All but one have been active in the last million years. The origin of the Canary Islands is not well established and local and regional geology features cannot be completely explained by the current models. The main aim of this study is to provide new data that help us to understand and constrain the archipelago's origin and tectonic evolution. The crustal structure under each station is obtained applying P-receiver function technique to the teleseismic P arrivals recorded by the broadband seismic network installed at the Canary Island by the Instituto Geográfico Nacional (IGN) and two temporary stations (MIDSEA and IRIS). We computed receiver functions using the Extended-Time Multitaper Frequency Domain Cross-Correlation Receiver Function (ET-MTRF) method. The results show that the crust is thicker, around 22 km, in the eastern islands (Fuerteventura and Lanzarote) than in the western ones (El Hierro, La Palma, Tenerife), around 17 km, with the exception of La Gomera island. This island, located in the west, exhibits similar crustal structure to Fuerteventura and Lanzarote. A discontinuity at 70-80 km, possibly the LAB (Lithosphere Asthenosphere Boundary) is clearly observed in all the stations. It appears that Moho depths do not track the LAB discontinuity.

A Steady-State Kalman Predictor-Based Filtering Strategy for Non-Overlapping Sub-Band Spectral Estimation

PubMed Central

Li, Zenghui; Xu, Bin; Yang, Jian; Song, Jianshe

2015-01-01

This paper focuses on suppressing spectral overlap for sub-band spectral estimation, with which we can greatly decrease the computational complexity of existing spectral estimation algorithms, such as nonlinear least squares spectral analysis and non-quadratic regularized sparse representation. Firstly, our study shows that the nominal ability of the high-order analysis filter to suppress spectral overlap is greatly weakened when filtering a finite-length sequence, because many meaningless zeros are used as samples in convolution operations. Next, an extrapolation-based filtering strategy is proposed to produce a series of estimates as the substitutions of the zeros and to recover the suppression ability. Meanwhile, a steady-state Kalman predictor is applied to perform a linearly-optimal extrapolation. Finally, several typical methods for spectral analysis are applied to demonstrate the effectiveness of the proposed strategy. PMID:25609038

Method of multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2004-01-06

A method of determining the properties of a sample from measured spectral data collected from the sample by performing a multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used to analyze X-ray spectral data generated by operating a Scanning Electron Microscope (SEM) with an attached Energy Dispersive Spectrometer (EDS).

Spectral and Temporal Laser Fluorescence Analysis Such as for Natural Aquatic Environments

NASA Technical Reports Server (NTRS)

Chekalyuk, Alexander (Inventor)

2015-01-01

An Advanced Laser Fluorometer (ALF) can combine spectrally and temporally resolved measurements of laser-stimulated emission (LSE) for characterization of dissolved and particulate matter, including fluorescence constituents, in liquids. Spectral deconvolution (SDC) analysis of LSE spectral measurements can accurately retrieve information about individual fluorescent bands, such as can be attributed to chlorophyll-a (Chl-a), phycobiliprotein (PBP) pigments, or chromophoric dissolved organic matter (CDOM), among others. Improved physiological assessments of photosynthesizing organisms can use SDC analysis and temporal LSE measurements to assess variable fluorescence corrected for SDC-retrieved background fluorescence. Fluorescence assessments of Chl-a concentration based on LSE spectral measurements can be improved using photo-physiological information from temporal measurements. Quantitative assessments of PBP pigments, CDOM, and other fluorescent constituents, as well as basic structural characterizations of photosynthesizing populations, can be performed using SDC analysis of LSE spectral measurements.

Classification of river water pollution using Hyperion data

NASA Astrophysics Data System (ADS)

Kar, Soumyashree; Rathore, V. S.; Champati ray, P. K.; Sharma, Richa; Swain, S. K.

2016-06-01

A novel attempt is made to use hyperspectral remote sensing to identify the spatial variability of metal pollutants present in river water. It was also attempted to classify the hyperspectral image - Earth Observation-1 (EO-1) Hyperion data of an 8 km stretch of the river Yamuna, near Allahabad city in India depending on its chemical composition. For validating image analysis results, a total of 10 water samples were collected and chemically analyzed using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Two different spectral libraries from field and image data were generated for the 10 sample locations. Advanced per-pixel supervised classifications such as Spectral Angle Mapper (SAM), SAM target finder using BandMax and Support Vector Machine (SVM) were carried out along with the unsupervised clustering procedure - Iterative Self-Organizing Data Analysis Technique (ISODATA). The results were compared and assessed with respect to ground data. Analytical Spectral Devices (ASD), Inc. spectroradiometer, FieldSpec 4 was used to generate the spectra of the water samples which were compiled into a spectral library and used for Spectral Absorption Depth (SAD) analysis. The spectral depth pattern of image and field spectral libraries was found to be highly correlated (correlation coefficient, R2 = 0.99) which validated the image analysis results with respect to the ground data. Further, we carried out a multivariate regression analysis to assess the varying concentrations of metal ions present in water based on the spectral depth of the corresponding absorption feature. Spectral Absorption Depth (SAD) analysis along with metal analysis of field data revealed the order in which the metals affected the river pollution, which was in conformity with the findings of Central Pollution Control Board (CPCB). Therefore, it is concluded that hyperspectral imaging provides opportunity that can be used for satellite based remote monitoring of water quality from space.

Automatic classification of spectral units in the Aristarchus plateau

NASA Astrophysics Data System (ADS)

Erard, S.; Le Mouelic, S.; Langevin, Y.

1999-09-01

A reduction scheme has been recently proposed for the NIR images of Clementine (Le Mouelic et al, JGR 1999). This reduction has been used to build an integrated UVvis-NIR image cube of the Aristarchus region, from which compositional and maturity variations can be studied (Pinet et al, LPSC 1999). We will present an analysis of this image cube, providing a classification in spectral types and spectral units. The image cube is processed with Gmode analysis using three different data sets: Normalized spectra provide a classification based mainly on spectral slope variations (ie. maturity and volcanic glasses). This analysis discriminates between craters plus ejecta, mare basalts, and DMD. Olivine-rich areas and Aristarchus central peak are also recognized. Continuum-removed spectra provide a classification more related to compositional variations, which correctly identifies olivine and pyroxenes-rich areas (in Aristarchus, Krieger, Schiaparelli\\ldots). A third analysis uses spectral parameters related to maturity and Fe composition (reflectance, 1 mu m band depth, and spectral slope) rather than intensities. It provides the most spatially consistent picture, but fails in detecting Vallis Schroeteri and DMDs. A supplementary unit, younger and rich in pyroxene, is found on Aristarchus south rim. In conclusion, Gmode analysis can discriminate between different spectral types already identified with more classic methods (PCA, linear mixing\\ldots). No previous assumption is made on the data structure, such as endmembers number and nature, or linear relationship between input variables. The variability of the spectral types is intrinsically accounted for, so that the level of analysis is always restricted to meaningful limits. A complete classification should integrate several analyses based on different sets of parameters. Gmode is therefore a powerful light toll to perform first look analysis of spectral imaging data. This research has been partly founded by the French Programme National de Planetologie.

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

Spectral analysis for GNSS coordinate time series using chirp Fourier transform

NASA Astrophysics Data System (ADS)

Feng, Shengtao; Bo, Wanju; Ma, Qingzun; Wang, Zifan

2017-12-01

Spectral analysis for global navigation satellite system (GNSS) coordinate time series provides a principal tool to understand the intrinsic mechanism that affects tectonic movements. Spectral analysis methods such as the fast Fourier transform, Lomb-Scargle spectrum, evolutionary power spectrum, wavelet power spectrum, etc. are used to find periodic characteristics in time series. Among spectral analysis methods, the chirp Fourier transform (CFT) with less stringent requirements is tested with synthetic and actual GNSS coordinate time series, which proves the accuracy and efficiency of the method. With the length of series only limited to even numbers, CFT provides a convenient tool for windowed spectral analysis. The results of ideal synthetic data prove CFT accurate and efficient, while the results of actual data show that CFT is usable to derive periodic information from GNSS coordinate time series.

Determination of awareness in patients with severe brain injury using EEG power spectral analysis

PubMed Central

Goldfine, Andrew M.; Victor, Jonathan D.; Conte, Mary M.; Bardin, Jonathan C.; Schiff, Nicholas D.

2011-01-01

Objective To determine whether EEG spectral analysis could be used to demonstrate awareness in patients with severe brain injury. Methods We recorded EEG from healthy controls and three patients with severe brain injury, ranging from minimally conscious state (MCS) to locked-in-state (LIS), while they were asked to imagine motor and spatial navigation tasks. We assessed EEG spectral differences from 4 to 24 Hz with univariate comparisons (individual frequencies) and multivariate comparisons (patterns across the frequency range). Results In controls, EEG spectral power differed at multiple frequency bands and channels during performance of both tasks compared to a resting baseline. As patterns of signal change were inconsistent between controls, we defined a positive response in patient subjects as consistent spectral changes across task performances. One patient in MCS and one in LIS showed evidence of motor imagery task performance, though with patterns of spectral change different from the controls. Conclusion EEG power spectral analysis demonstrates evidence for performance of mental imagery tasks in healthy controls and patients with severe brain injury. Significance EEG power spectral analysis can be used as a flexible bedside tool to demonstrate awareness in brain-injured patients who are otherwise unable to communicate. PMID:21514214

An Improved Spectral Analysis Method for Fatigue Damage Assessment of Details in Liquid Cargo Tanks

NASA Astrophysics Data System (ADS)

Zhao, Peng-yuan; Huang, Xiao-ping

2018-03-01

Errors will be caused in calculating the fatigue damages of details in liquid cargo tanks by using the traditional spectral analysis method which is based on linear system, for the nonlinear relationship between the dynamic stress and the ship acceleration. An improved spectral analysis method for the assessment of the fatigue damage in detail of a liquid cargo tank is proposed in this paper. Based on assumptions that the wave process can be simulated by summing the sinusoidal waves in different frequencies and the stress process can be simulated by summing the stress processes induced by these sinusoidal waves, the stress power spectral density (PSD) is calculated by expanding the stress processes induced by the sinusoidal waves into Fourier series and adding the amplitudes of each harmonic component with the same frequency. This analysis method can take the nonlinear relationship into consideration and the fatigue damage is then calculated based on the PSD of stress. Take an independent tank in an LNG carrier for example, the accuracy of the improved spectral analysis method is proved much better than that of the traditional spectral analysis method by comparing the calculated damage results with the results calculated by the time domain method. The proposed spectral analysis method is more accurate in calculating the fatigue damages in detail of ship liquid cargo tanks.

Cycles and trends in the δ18O and δ13C records over the Jurassic and Early Cretaceous

NASA Astrophysics Data System (ADS)

Martinez, Mathieu; Dera, Guillaume

2015-04-01

The million-year fluctuations of the Mesozoic climate are explored through spectral analyses performed on an exhaustive compilation of δ18O and δ13C data measured on belemnite rostra. The data include more than 3500 data points, all coming from Western Tethys and Euro-boreal domains, and covering a time interval spanning 76 Myr from the Sinemurian (~197 Ma; Early Jurassic) to the Aptian (~123 Ma; Early Cretaceous) with an average sample step of ~0.04 Myr. Spectral analyses are performed using the multi-taper method and the evolutive Fast Fourier Transform in order to get an accurate estimate of significant periods and their evolution during geological times. The age uncertainties of the Geological Time Scale 2012 are taken into account to assess the impact of these uncertainties on the identification of the significant periods. After implementing an error model that simulates the uncertainties of the Geological Time Scale, two periods remains significant: the δ13C displays a high-amplitude period at 9.1 Myr, while the δ18O displays a high-amplitude period at 16.4 Myr. The 16.4-Myr period is only expressed in the Early and Middle Jurassic, with maximum amplitudes reached during the 'Toarcian Plateau' (Dera et al., 2011). It is probably a consequence of the activity of the Karoo-Ferrar Large Igneous Province and is an event in the δ18O rather than a true cycle. The 9.1-Myr period displays a spectacular continuity from the Toarcian to the Aptian, and could be related to this intriguing 9.1-Myr cycle observed in the δ13C from the Cenozoic, related to a Myr-amplitude modulation of the eccentricity cycles (Boulila et al., 2012). The δ13C in the Western Tethys thus appears to have a very rhythmic behaviour, interpreted here as a long-term orbital modulation of moisture and heat transfer from equatorial to higher latitudes, modulating in return continental weathering, nutrient and detrital exports to basins, neritic vs. pelagic productivity and finally preservation of organic matter in the oceanic basins. References: Dera, G., Brigaud, B., Monna, F., Laffont, R., Pucéat, E., Deconinck, J.-F., Pellenard, P., Joachimski, M.M. and Durlet, C., 2011. Climatic ups and downs in a disturbed Jurassic world. Geology 39(3), 215-218. Boulila, S., Galbrun, B., Laskar, J. and Pälike, H., 2012. A ~9 myr cycle in Cenozoic δ13C record and long-term orbital eccentricity modulation: Is there a link? Earth and Planetary Science Letters 317-318, 273-281.

Advances in Global Adjoint Tomography -- Massive Data Assimilation

NASA Astrophysics Data System (ADS)

Ruan, Y.; Lei, W.; Bozdag, E.; Lefebvre, M. P.; Smith, J. A.; Krischer, L.; Tromp, J.

2015-12-01

Azimuthal anisotropy and anelasticity are key to understanding a myriad of processes in Earth's interior. Resolving these properties requires accurate simulations of seismic wave propagation in complex 3-D Earth models and an iterative inversion strategy. In the wake of successes in regional studies(e.g., Chen et al., 2007; Tape et al., 2009, 2010; Fichtner et al., 2009, 2010; Chen et al.,2010; Zhu et al., 2012, 2013; Chen et al., 2015), we are employing adjoint tomography based on a spectral-element method (Komatitsch & Tromp 1999, 2002) on a global scale using the supercomputer ''Titan'' at Oak Ridge National Laboratory. After 15 iterations, we have obtained a high-resolution transversely isotropic Earth model (M15) using traveltime data from 253 earthquakes. To obtain higher resolution images of the emerging new features and to prepare the inversion for azimuthal anisotropy and anelasticity, we expanded the original dataset with approximately 4,220 additional global earthquakes (Mw5.5-7.0) --occurring between 1995 and 2014-- and downloaded 300-minute-long time series for all available data archived at the IRIS Data Management Center, ORFEUS, and F-net. Ocean Bottom Seismograph data from the last decade are also included to maximize data coverage. In order to handle the huge dataset and solve the I/O bottleneck in global adjoint tomography, we implemented a python-based parallel data processing workflow based on the newly developed Adaptable Seismic Data Format (ASDF). With the help of the data selection tool MUSTANG developed by IRIS, we cleaned our dataset and assembled event-based ASDF files for parallel processing. We have started Centroid Moment Tensors (CMT) inversions for all 4,220 earthquakes with the latest model M15, and selected high-quality data for measurement. We will statistically investigate each channel using synthetic seismograms calculated in M15 for updated CMTs and identify problematic channels. In addition to data screening, we also modified the conventional multi-taper method to obtain better frequency-dependent measurements of surface-wave phase and amplitude anomalies, and therefore more accurate adjoint sources, which are particularly important for anelastic tomography. We present a summary of these data culling and processing procedures for global adjoint tomography.

Ambient noise adjoint tomography for a linear array in North China

NASA Astrophysics Data System (ADS)

Zhang, C.; Yao, H.; Liu, Q.; Yuan, Y. O.; Zhang, P.; Feng, J.; Fang, L.

2017-12-01

Ambient noise tomography based on dispersion data and ray theory has been widely utilized for imaging crustal structures. In order to improve the inversion accuracy, ambient noise tomography based on the 3D adjoint approach or full waveform inversion has been developed recently, however, the computational cost is tremendous. In this study we present 2D ambient noise adjoint tomography for a linear array in north China with significant computational efficiency compared to 3D ambient noise adjoint tomography. During the preprocessing, we first convert the observed data in 3D media, i.e., surface-wave empirical Green's functions (EGFs) from ambient noise cross-correlation, to the reconstructed EGFs in 2D media using a 3D/2D transformation scheme. Different from the conventional steps of measuring phase dispersion, the 2D adjoint tomography refines 2D shear wave speeds along the profile directly from the reconstructed Rayleigh wave EGFs in the period band 6-35s. With the 2D initial model extracted from the 3D model from traditional ambient noise tomography, adjoint tomography updates the model by minimizing the frequency-dependent Rayleigh wave traveltime misfits between the reconstructed EGFs and synthetic Green function (SGFs) in 2D media generated by the spectral-element method (SEM), with a preconditioned conjugate gradient method. The multitaper traveltime difference measurement is applied in four period bands during the inversion: 20-35s, 15-30s, 10-20s and 6-15s. The recovered model shows more detailed crustal structures with pronounced low velocity anomaly in the mid-lower crust beneath the junction of Taihang Mountains and Yin-Yan Mountains compared with the initial model. This low velocity structure may imply the possible intense crust-mantle interactions, probably associated with the magmatic underplating during the Mesozoic to Cenozoic evolution of the region. To our knowledge, it's first time that ambient noise adjoint tomography is implemented in 2D media. Considering the intensive computational cost and storage of 3D adjoint tomography, this 2D ambient noise adjoint tomography has potential advantages to get high-resolution 2D crustal structures with limited computational resource.

Multispectral analysis tools can increase utility of RGB color images in histology

NASA Astrophysics Data System (ADS)

Fereidouni, Farzad; Griffin, Croix; Todd, Austin; Levenson, Richard

2018-04-01

Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

Blast investigation by fast multispectral radiometric analysis

NASA Astrophysics Data System (ADS)

Devir, A. D.; Bushlin, Y.; Mendelewicz, I.; Lessin, A. B.; Engel, M.

2011-06-01

Knowledge regarding the processes involved in blasts and detonations is required in various applications, e.g. missile interception, blasts of high-explosive materials, final ballistics and IED identification. Blasts release large amount of energy in short time duration. Some part of this energy is released as intense radiation in the optical spectral bands. This paper proposes to measure the blast radiation by a fast multispectral radiometer. The measurement is made, simultaneously, in appropriately chosen spectral bands. These spectral bands provide extensive information on the physical and chemical processes that govern the blast through the time-dependence of the molecular and aerosol contributions to the detonation products. Multi-spectral blast measurements are performed in the visible, SWIR and MWIR spectral bands. Analysis of the cross-correlation between the measured multi-spectral signals gives the time dependence of the temperature, aerosol and gas composition of the blast. Farther analysis of the development of these quantities in time may indicate on the order of the detonation and amount and type of explosive materials. Examples of analysis of measured explosions are presented to demonstrate the power of the suggested fast multispectral radiometric analysis approach.

Spectral analysis using the CCD Chirp Z-transform

NASA Technical Reports Server (NTRS)

Eversole, W. L.; Mayer, D. J.; Bosshart, P. W.; Dewit, M.; Howes, C. R.; Buss, D. D.

1978-01-01

The charge coupled device (CCD) Chirp Z transformation (CZT) spectral analysis techniques were reviewed and results on state-of-the-art CCD CZT technology are presented. The CZT algorithm was examined and the advantages of CCD implementation are discussed. The sliding CZT which is useful in many spectral analysis applications is described, and the performance limitations of the CZT are studied.

A new automated spectral feature extraction method and its application in spectral classification and defective spectra recovery

NASA Astrophysics Data System (ADS)

Wang, Ke; Guo, Ping; Luo, A.-Li

2017-03-01

Spectral feature extraction is a crucial procedure in automated spectral analysis. This procedure starts from the spectral data and produces informative and non-redundant features, facilitating the subsequent automated processing and analysis with machine-learning and data-mining techniques. In this paper, we present a new automated feature extraction method for astronomical spectra, with application in spectral classification and defective spectra recovery. The basic idea of our approach is to train a deep neural network to extract features of spectra with different levels of abstraction in different layers. The deep neural network is trained with a fast layer-wise learning algorithm in an analytical way without any iterative optimization procedure. We evaluate the performance of the proposed scheme on real-world spectral data. The results demonstrate that our method is superior regarding its comprehensive performance, and the computational cost is significantly lower than that for other methods. The proposed method can be regarded as a new valid alternative general-purpose feature extraction method for various tasks in spectral data analysis.

Spectral analysis of variable-length coded digital signals

NASA Astrophysics Data System (ADS)

Cariolaro, G. L.; Pierobon, G. L.; Pupolin, S. G.

1982-05-01

A spectral analysis is conducted for a variable-length word sequence by an encoder driven by a stationary memoryless source. A finite-state sequential machine is considered as a model of the line encoder, and the spectral analysis of the encoded message is performed under the assumption that the sourceword sequence is composed of independent identically distributed words. Closed form expressions for both the continuous and discrete parts of the spectral density are derived in terms of the encoder law and sourceword statistics. The jump part exhibits jumps at multiple integers of per lambda(sub 0)T, where lambda(sub 0) is the greatest common divisor of the possible codeword lengths, and T is the symbol period. The derivation of the continuous part can be conveniently factorized, and the theory is applied to the spectral analysis of BnZS and HDBn codes.

Spectral classifying base on color of live corals and dead corals covered with algae

NASA Astrophysics Data System (ADS)

Nurdin, Nurjannah; Komatsu, Teruhisa; Barille, Laurent; Akbar, A. S. M.; Sawayama, Shuhei; Fitrah, Muh. Nur; Prasyad, Hermansyah

2016-05-01

Pigments in the host tissues of corals can make a significant contribution to their spectral signature and can affect their apparent color as perceived by a human observer. The aim of this study is classifying the spectral reflectance of corals base on different color. It is expected that they can be used as references in discriminating between live corals, dead coral covered with algae Spectral reflectance data was collected in three small islands, Spermonde Archipelago, Indonesia by using a hyperspectral radiometer underwater. First and second derivative analysis resolved the wavelength locations of dominant features contributing to reflectance in corals and support the distinct differences in spectra among colour existed. Spectral derivative analysis was used to determine the specific wavelength regions ideal for remote identification of substrate type. The analysis results shown that yellow, green, brown and violet live corals are spectrally separable from each other, but they are similar with dead coral covered with algae spectral.

The Spectral Image Processing System (SIPS): Software for integrated analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

1992-01-01

The Spectral Image Processing System (SIPS) is a software package developed by the Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, in response to a perceived need to provide integrated tools for analysis of imaging spectrometer data both spectrally and spatially. SIPS was specifically designed to deal with data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the High Resolution Imaging Spectrometer (HIRIS), but was tested with other datasets including the Geophysical and Environmental Research Imaging Spectrometer (GERIS), GEOSCAN images, and Landsat TM. SIPS was developed using the 'Interactive Data Language' (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system to provide rapid analysis of entire imaging spectrometer datasets. SIPS allows analysis of single or multiple imaging spectrometer data segments at full spatial and spectral resolution. It also allows visualization and interactive analysis of image cubes derived from quantitative analysis procedures such as absorption band characterization and spectral unmixing. SIPS consists of three modules: SIPS Utilities, SIPS_View, and SIPS Analysis. SIPS version 1.1 is described below.

Hierarchical Processing of Auditory Objects in Humans

PubMed Central

Kumar, Sukhbinder; Stephan, Klaas E; Warren, Jason D; Friston, Karl J; Griffiths, Timothy D

2007-01-01

This work examines the computational architecture used by the brain during the analysis of the spectral envelope of sounds, an important acoustic feature for defining auditory objects. Dynamic causal modelling and Bayesian model selection were used to evaluate a family of 16 network models explaining functional magnetic resonance imaging responses in the right temporal lobe during spectral envelope analysis. The models encode different hypotheses about the effective connectivity between Heschl's Gyrus (HG), containing the primary auditory cortex, planum temporale (PT), and superior temporal sulcus (STS), and the modulation of that coupling during spectral envelope analysis. In particular, we aimed to determine whether information processing during spectral envelope analysis takes place in a serial or parallel fashion. The analysis provides strong support for a serial architecture with connections from HG to PT and from PT to STS and an increase of the HG to PT connection during spectral envelope analysis. The work supports a computational model of auditory object processing, based on the abstraction of spectro-temporal “templates” in the PT before further analysis of the abstracted form in anterior temporal lobe areas. PMID:17542641

An Analysis of Periodic Components in BL Lac Object S5 0716 +714 with MUSIC Method

NASA Astrophysics Data System (ADS)

Tang, J.

2012-01-01

Multiple signal classification (MUSIC) algorithms are introduced to the estimation of the period of variation of BL Lac objects.The principle of MUSIC spectral analysis method and theoretical analysis of the resolution of frequency spectrum using analog signals are included. From a lot of literatures, we have collected a lot of effective observation data of BL Lac object S5 0716 + 714 in V, R, I bands from 1994 to 2008. The light variation periods of S5 0716 +714 are obtained by means of the MUSIC spectral analysis method and periodogram spectral analysis method. There exist two major periods: (3.33±0.08) years and (1.24±0.01) years for all bands. The estimation of the period of variation of the algorithm based on the MUSIC spectral analysis method is compared with that of the algorithm based on the periodogram spectral analysis method. It is a super-resolution algorithm with small data length, and could be used to detect the period of variation of weak signals.

Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding

PubMed Central

Lobos, Gustavo A.; Poblete-Echeverría, Carlos

2017-01-01

This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules. PMID:28119705

Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding.

PubMed

Lobos, Gustavo A; Poblete-Echeverría, Carlos

2016-01-01

This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules.

Robust and transferable quantification of NMR spectral quality using IROC analysis

NASA Astrophysics Data System (ADS)

Zambrello, Matthew A.; Maciejewski, Mark W.; Schuyler, Adam D.; Weatherby, Gerard; Hoch, Jeffrey C.

2017-12-01

Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.

SPAM- SPECTRAL ANALYSIS MANAGER (DEC VAX/VMS VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

Simulation of time-dispersion spectral device with sample spectra accumulation

NASA Astrophysics Data System (ADS)

Zhdanov, Arseny; Khansuvarov, Ruslan; Korol, Georgy

2014-09-01

This research is conducted in order to design a spectral device for light sources power spectrum analysis. The spectral device should process radiation from sources, direct contact with radiation of which is either impossible or undesirable. Such sources include jet blast of an aircraft, optical radiation in metallurgy and textile industry. In proposed spectral device optical radiation is guided out of unfavorable environment via a piece of optical fiber with high dispersion. It is necessary for analysis to make samples of analyzed radiation as short pulses. Dispersion properties of such optical fiber cause spectral decomposition of input optical pulses. The faster time of group delay vary the stronger the spectral decomposition effect. This effect allows using optical fiber with high dispersion as a major element of proposed spectral device. Duration of sample must be much shorter than group delay time difference of a dispersive system. In the given frequency range this characteristic has to be linear. The frequency range is 400 … 500 THz for typical optical fiber. Using photonic-crystal fiber (PCF) gives much wider spectral range for analysis. In this paper we propose simulation of single pulse transmission through dispersive system with linear dispersion characteristic and quadratic-detected output responses accumulation. During simulation we propose studying influence of optical fiber dispersion characteristic angle on spectral measurement results. We also consider pulse duration and group delay time difference impact on output pulse shape and duration. Results show the most suitable dispersion characteristic that allow choosing the structure of PCF - major element of time-dispersion spectral analysis method and required number of samples for reliable assessment of measured spectrum.

A statistical evaluation of spectral fingerprinting methods using analysis of variance and principal component analysis

USDA-ARS?s Scientific Manuscript database

Six methods were compared with respect to spectral fingerprinting of a well-characterized series of broccoli samples. Spectral fingerprints were acquired for finely-powdered solid samples using Fourier transform-infrared (IR) and Fourier transform-near infrared (NIR) spectrometry and for aqueous met...

What drives high flow events in the Swiss Alps? Recent developments in wavelet spectral analysis and their application to hydrology

NASA Astrophysics Data System (ADS)

Schaefli, B.; Maraun, D.; Holschneider, M.

2007-12-01

Extreme hydrological events are often triggered by exceptional co-variations of the relevant hydrometeorological processes and in particular by exceptional co-oscillations at various temporal scales. Wavelet and cross wavelet spectral analysis offers promising time-scale resolved analysis methods to detect and analyze such exceptional co-oscillations. This paper presents the state-of-the-art methods of wavelet spectral analysis, discusses related subtleties, potential pitfalls and recently developed solutions to overcome them and shows how wavelet spectral analysis, if combined to a rigorous significance test, can lead to reliable new insights into hydrometeorological processes for real-world applications. The presented methods are applied to detect potentially flood triggering situations in a high Alpine catchment for which a recent re-estimation of design floods encountered significant problems simulating the observed high flows. For this case study, wavelet spectral analysis of precipitation, temperature and discharge offers a powerful tool to help detecting potentially flood producing meteorological situations and to distinguish between different types of floods with respect to the prevailing critical hydrometeorological conditions. This opens very new perspectives for the analysis of model performances focusing on the occurrence and non-occurrence of different types of high flow events. Based on the obtained results, the paper summarizes important recommendations for future applications of wavelet spectral analysis in hydrology.

Digital techniques for ULF wave polarization analysis

NASA Technical Reports Server (NTRS)

Arthur, C. W.

1979-01-01

Digital power spectral and wave polarization analysis are powerful techniques for studying ULF waves in the earth's magnetosphere. Four different techniques for using the spectral matrix to perform such an analysis have been presented in the literature. Three of these techniques are similar in that they require transformation of the spectral matrix to the principal axis system prior to performing the polarization analysis. The differences in the three techniques lie in the manner in which determine this transformation. A comparative study of these three techniques using both simulated and real data has shown them to be approximately equal in quality of performance. The fourth technique does not require transformation of the spectral matrix. Rather, it uses the measured spectral matrix and state vectors for a desired wave type to design a polarization detector function in the frequency domain. The design of various detector functions and their application to both simulated and real data will be presented.

Global spectral graph wavelet signature for surface analysis of carpal bones

NASA Astrophysics Data System (ADS)

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A.

2018-02-01

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

Global spectral graph wavelet signature for surface analysis of carpal bones.

PubMed

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A

2018-02-05

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

GEOS-2 C-band radar system project. Spectral analysis as related to C-band radar data analysis

NASA Technical Reports Server (NTRS)

1972-01-01

Work performed on spectral analysis of data from the C-band radars tracking GEOS-2 and on the development of a data compaction method for the GEOS-2 C-band radar data is described. The purposes of the spectral analysis study were to determine the optimum data recording and sampling rates for C-band radar data and to determine the optimum method of filtering and smoothing the data. The optimum data recording and sampling rate is defined as the rate which includes an optimum compromise between serial correlation and the effects of frequency folding. The goal in development of a data compaction method was to reduce to a minimum the amount of data stored, while maintaining all of the statistical information content of the non-compacted data. A digital computer program for computing estimates of the power spectral density function of sampled data was used to perform the spectral analysis study.

Different techniques of multispectral data analysis for vegetation fraction retrieval

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Georgiev, Georgi

2012-07-01

Vegetation monitoring is one of the most important applications of remote sensing technologies. In respect to farmlands, the assessment of crop condition constitutes the basis of growth, development, and yield processes monitoring. Plant condition is defined by a set of biometric variables, such as density, height, biomass amount, leaf area index, and etc. The canopy cover fraction is closely related to these variables, and is state-indicative of the growth process. At the same time it is a defining factor of the soil-vegetation system spectral signatures. That is why spectral mixtures decomposition is a primary objective in remotely sensed data processing and interpretation, specifically in agricultural applications. The actual usefulness of the applied methods depends on their prediction reliability. The goal of this paper is to present and compare different techniques for quantitative endmember extraction from soil-crop patterns reflectance. These techniques include: linear spectral unmixing, two-dimensional spectra analysis, spectral ratio analysis (vegetation indices), spectral derivative analysis (red edge position), colorimetric analysis (tristimulus values sum, chromaticity coordinates and dominant wavelength). The objective is to reveal their potential, accuracy and robustness for plant fraction estimation from multispectral data. Regression relationships have been established between crop canopy cover and various spectral estimators.

Planck 2013 results. IX. HFI spectral response

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bock, J. J.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bridges, M.; Bucher, M.; Burigana, C.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chen, X.; Chiang, H. C.; Chiang, L.-Y.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Dupac, X.; Efstathiou, G.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Finelli, F.; Forni, O.; Frailis, M.; Franceschi, E.; Galeotta, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Hanson, D.; Harrison, D.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Laureijs, R. J.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Leroy, C.; Lesgourgues, J.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Mandolesi, N.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Mazzotta, P.; McGehee, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; North, C.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rusholme, B.; Santos, D.; Savini, G.; Scott, D.; Shellard, E. P. S.; Spencer, L. D.; Starck, J.-L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Tavagnacco, D.; Terenzi, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Yvon, D.; Zacchei, A.; Zonca, A.

2014-11-01

The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission tests was to measure the relative spectral response (includingthe level of out-of-band signal rejection) of all HFI detectors to a known source of electromagnetic radiation individually. This was determined by measuring the interferometric output of a continuously scanned Fourier transform spectrometer with all HFI detectors. As there is no on-board spectrometer within HFI, the ground-based spectral response experiments provide the definitive data set for the relative spectral calibration of the HFI. Knowledge of the relative variations in the spectral response between HFI detectors allows for a more thorough analysis of the HFI data. The spectral response of the HFI is used in Planck data analysis and component separation, this includes extraction of CO emission observed within Planck bands, dust emission, Sunyaev-Zeldovich sources, and intensity to polarization leakage. The HFI spectral response data have also been used to provide unit conversion and colour correction analysis tools. While previous papers describe the pre-flight experiments conducted on the Planck HFI, this paper focusses on the analysis of the pre-flight spectral response measurements and the derivation of data products, e.g. band-average spectra, unit conversion coefficients, and colour correction coefficients, all with related uncertainties. Verifications of the HFI spectral response data are provided through comparisons with photometric HFI flight data. This validation includes use of HFI zodiacal emission observations to demonstrate out-of-band spectral signal rejection better than 108. The accuracy of the HFI relative spectral response data is verified through comparison with complementary flight-data based unit conversion coefficients and colour correction coefficients. These coefficients include those based upon HFI observations of CO, dust, and Sunyaev-Zeldovich emission. General agreement is observed between the ground-based spectral characterization of HFI and corresponding in-flight observations, within the quoted uncertainty of each; explanations are provided for any discrepancies.

Acoustic signature of thunder from seismic records

NASA Astrophysics Data System (ADS)

Kappus, Mary E.; Vernon, Frank L.

1991-06-01

Thunder, the sound wave through the air associated with lightning, transfers sufficient energy to the ground to trigger seismometers set to record regional earthquakes. The acoustic signature recorded on seismometers, in the form of ground velocity as a function of time, contains the same type features as pressure variations recorded with microphones in air. At a seismic station in Kislovodsk, USSR, a nearly direct lightning strike caused electronic failure of borehole instruments while leaving a brief impulsive acoustic signature on the surface instruments. The peak frequency of 25-55 Hz is consistent with previously published values for cloud-to-ground lightning strikes, but spectra from this station are contaminated by very strong wind noise in this band. A thunderstorm near a similar station in Karasu triggered more than a dozen records of individual lightning strikes during a 2-hour period. The spectra for these events are fairly broadband, with peaks at low frequencies, varying from 6 to 13 Hz. The spectra were all computed by multitaper analysis, which deals appropriately with the nonstationary thunder signal. These independent measurements of low-frequency peaks corroborate the occasional occurrences in traditional microphone records, but a theory concerning the physical mechanism to account for them is still in question. Examined separately, the individual claps in each record have similar frequency distributions, discounting a need for multiple mechanisms to explain different phases of the thunder sequence. Particle motion, determined from polarization analysis of the three-component records, is predominantly vertical downward, with smaller horizontal components indicative of the direction to the lightning bolt. In three of the records the azimuth to the lightning bolt changes with time, confirming a significant horizontal component to the lightning channel itself.

SpecViz: Interactive Spectral Data Analysis

NASA Astrophysics Data System (ADS)

Earl, Nicholas Michael; STScI

2016-06-01

The astronomical community is about to enter a new generation of scientific enterprise. With next-generation instrumentation and advanced capabilities, the need has arisen to equip astronomers with the necessary tools to deal with large, multi-faceted data. The Space Telescope Science Institute has initiated a data analysis forum for the creation, development, and maintenance of software tools for the interpretation of these new data sets. SpecViz is a spectral 1-D interactive visualization and analysis application built with Python in an open source development environment. A user-friendly GUI allows for a fast, interactive approach to spectral analysis. SpecViz supports handling of unique and instrument-specific data, incorporation of advanced spectral unit handling and conversions in a flexible, high-performance interactive plotting environment. Active spectral feature analysis is possible through interactive measurement and statistical tools. It can be used to build wide-band SEDs, with the capability of combining or overplotting data products from various instruments. SpecViz sports advanced toolsets for filtering and detrending spectral lines; identifying, isolating, and manipulating spectral features; as well as utilizing spectral templates for renormalizing data in an interactive way. SpecViz also includes a flexible model fitting toolset that allows for multi-component models, as well as custom models, to be used with various fitting and decomposition routines. SpecViz also features robust extension via custom data loaders and connection to the central communication system underneath the interface for more advanced control. Incorporation with Jupyter notebooks via connection with the active iPython kernel allows for SpecViz to be used in addition to a user’s normal workflow without demanding the user drastically alter their method of data analysis. In addition, SpecViz allows the interactive analysis of multi-object spectroscopy in the same straight-forward, consistent way. Through the development of such tools, STScI hopes to unify astronomical data analysis software for JWST and other instruments, allowing for efficient, reliable, and consistent scientific results.

Spectral analysis software improves confidence in plant and soil water stable isotope analyses performed by isotope ratio infrared spectroscopy (IRIS).

PubMed

West, A G; Goldsmith, G R; Matimati, I; Dawson, T E

2011-08-30

Previous studies have demonstrated the potential for large errors to occur when analyzing waters containing organic contaminants using isotope ratio infrared spectroscopy (IRIS). In an attempt to address this problem, IRIS manufacturers now provide post-processing spectral analysis software capable of identifying samples with the types of spectral interference that compromises their stable isotope analysis. Here we report two independent tests of this post-processing spectral analysis software on two IRIS systems, OA-ICOS (Los Gatos Research Inc.) and WS-CRDS (Picarro Inc.). Following a similar methodology to a previous study, we cryogenically extracted plant leaf water and soil water and measured the δ(2)H and δ(18)O values of identical samples by isotope ratio mass spectrometry (IRMS) and IRIS. As an additional test, we analyzed plant stem waters and tap waters by IRMS and IRIS in an independent laboratory. For all tests we assumed that the IRMS value represented the "true" value against which we could compare the stable isotope results from the IRIS methods. Samples showing significant deviations from the IRMS value (>2σ) were considered to be contaminated and representative of spectral interference in the IRIS measurement. Over the two studies, 83% of plant species were considered contaminated on OA-ICOS and 58% on WS-CRDS. Post-analysis, spectra were analyzed using the manufacturer's spectral analysis software, in order to see if the software correctly identified contaminated samples. In our tests the software performed well, identifying all the samples with major errors. However, some false negatives indicate that user evaluation and testing of the software are necessary. Repeat sampling of plants showed considerable variation in the discrepancies between IRIS and IRMS. As such, we recommend that spectral analysis of IRIS data must be incorporated into standard post-processing routines. Furthermore, we suggest that the results from spectral analysis be included when reporting stable isotope data from IRIS. Copyright © 2011 John Wiley & Sons, Ltd.

Highly sensitive index of sympathetic activity based on time-frequency spectral analysis of electrodermal activity.

PubMed

Posada-Quintero, Hugo F; Florian, John P; Orjuela-Cañón, Álvaro D; Chon, Ki H

2016-09-01

Time-domain indices of electrodermal activity (EDA) have been used as a marker of sympathetic tone. However, they often show high variation between subjects and low consistency, which has precluded their general use as a marker of sympathetic tone. To examine whether power spectral density analysis of EDA can provide more consistent results, we recently performed a variety of sympathetic tone-evoking experiments (43). We found significant increase in the spectral power in the frequency range of 0.045 to 0.25 Hz when sympathetic tone-evoking stimuli were induced. The sympathetic tone assessed by the power spectral density of EDA was found to have lower variation and more sensitivity for certain, but not all, stimuli compared with the time-domain analysis of EDA. We surmise that this lack of sensitivity in certain sympathetic tone-inducing conditions with time-invariant spectral analysis of EDA may lie in its inability to characterize time-varying dynamics of the sympathetic tone. To overcome the disadvantages of time-domain and time-invariant power spectral indices of EDA, we developed a highly sensitive index of sympathetic tone, based on time-frequency analysis of EDA signals. Its efficacy was tested using experiments designed to elicit sympathetic dynamics. Twelve subjects underwent four tests known to elicit sympathetic tone arousal: cold pressor, tilt table, stand test, and the Stroop task. We hypothesize that a more sensitive measure of sympathetic control can be developed using time-varying spectral analysis. Variable frequency complex demodulation, a recently developed technique for time-frequency analysis, was used to obtain spectral amplitudes associated with EDA. We found that the time-varying spectral frequency band 0.08-0.24 Hz was most responsive to stimulation. Spectral power for frequencies higher than 0.24 Hz were determined to be not related to the sympathetic dynamics because they comprised less than 5% of the total power. The mean value of time-varying spectral amplitudes in the frequency band 0.08-0.24 Hz were used as the index of sympathetic tone, termed TVSymp. TVSymp was found to be overall the most sensitive to the stimuli, as evidenced by a low coefficient of variation (0.54), and higher consistency (intra-class correlation, 0.96) and sensitivity (Youden's index > 0.75), area under the receiver operating characteristic (ROC) curve (>0.8, accuracy > 0.88) compared with time-domain and time-invariant spectral indices, including heart rate variability. Copyright © 2016 the American Physiological Society.

Spectral Analysis of Rich Network Topology in Social Networks

ERIC Educational Resources Information Center

Wu, Leting

2013-01-01

Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

A practical approach to spectral calibration of short wavelength infrared hyper-spectral imaging systems

NASA Astrophysics Data System (ADS)

Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2010-02-01

Near-infrared spectroscopy is a promising, rapidly developing, reliable and noninvasive technique, used extensively in the biomedicine and in pharmaceutical industry. With the introduction of acousto-optic tunable filters (AOTF) and highly sensitive InGaAs focal plane sensor arrays, real-time high resolution hyper-spectral imaging has become feasible for a number of new biomedical in vivo applications. However, due to the specificity of the AOTF technology and lack of spectral calibration standardization, maintaining long-term stability and compatibility of the acquired hyper-spectral images across different systems is still a challenging problem. Efficiently solving both is essential as the majority of methods for analysis of hyper-spectral images relay on a priori knowledge extracted from large spectral databases, serving as the basis for reliable qualitative or quantitative analysis of various biological samples. In this study, we propose and evaluate fast and reliable spectral calibration of hyper-spectral imaging systems in the short wavelength infrared spectral region. The proposed spectral calibration method is based on light sources or materials, exhibiting distinct spectral features, which enable robust non-rigid registration of the acquired spectra. The calibration accounts for all of the components of a typical hyper-spectral imaging system such as AOTF, light source, lens and optical fibers. The obtained results indicated that practical, fast and reliable spectral calibration of hyper-spectral imaging systems is possible, thereby assuring long-term stability and inter-system compatibility of the acquired hyper-spectral images.

Preliminary Results of a Magnetotelluric Survey in the Center of Hawaii Island

NASA Astrophysics Data System (ADS)

Lienert, B. R.; Thomas, D. M.; Wallin, E.

2014-12-01

From 2013 up to the present we have been recording magnetotelluric (MT) data at 25 sites in a 35x25 km region (elev. 1943 m) on the saddle between the active volcano of Mauna Loa (4169 m) and the dormant volcano of Mauna Kea (4205 m) on Hawai'i Island. The MT data, particularly the electric fields, are frequently contaminated by spurious components that are not due to the plane-wave magnetic signals required for derivation of the MT impedance tensor. We therefore developed interactive graphical software (MTPlot) to plot and analyze the MT signals in the field. MTPlot allows us to quickly examine records in both the time and frequency domain to in order to judge their quality. It also transforms the data into estimates of apparent resistivity and their error in the frequency range 0.001-500 Hz. This has proved very useful for selecting suitable records for subsequent analysis. We then use multi-taper remote reference processing to obtain our final apparent resistivity estimates and their errors. We present preliminary results of one and two dimensional modeling of these estimates to obtain the three-dimensional distribution of subsurface resistivities down to depths of 5 km. The results are compared to temperatures and properties of cores obtained when we drilled a research hole to a depth of 1760 m in this same region. We shall discuss how our results relate to the extent of the fresh-water and geothermal energy reservoirs that we discovered during drilling.

Power Spectral Density Error Analysis of Spectral Subtraction Type of Speech Enhancement Methods

NASA Astrophysics Data System (ADS)

Händel, Peter

2006-12-01

A theoretical framework for analysis of speech enhancement algorithms is introduced for performance assessment of spectral subtraction type of methods. The quality of the enhanced speech is related to physical quantities of the speech and noise (such as stationarity time and spectral flatness), as well as to design variables of the noise suppressor. The derived theoretical results are compared with the outcome of subjective listening tests as well as successful design strategies, performed by independent research groups.

[Analysis of software for identifying spectral line of laser-induced breakdown spectroscopy based on LabVIEW].

PubMed

Hu, Zhi-yu; Zhang, Lei; Ma, Wei-guang; Yan, Xiao-juan; Li, Zhi-xin; Zhang, Yong-zhi; Wang, Le; Dong, Lei; Yin, Wang-bao; Jia, Suo-tang

2012-03-01

Self-designed identifying software for LIBS spectral line was introduced. Being integrated with LabVIEW, the soft ware can smooth spectral lines and pick peaks. The second difference and threshold methods were employed. Characteristic spectrum of several elements matches the NIST database, and realizes automatic spectral line identification and qualitative analysis of the basic composition of sample. This software can analyze spectrum handily and rapidly. It will be a useful tool for LIBS.

Cardiovascular response to acute stress in freely moving rats: time-frequency analysis.

PubMed

Loncar-Turukalo, Tatjana; Bajic, Dragana; Japundzic-Zigon, Nina

2008-01-01

Spectral analysis of cardiovascular series is an important tool for assessing the features of the autonomic control of the cardiovascular system. In this experiment Wistar rats ecquiped with intraarterial catheter for blood pressure (BP) recording were exposed to stress induced by blowing air. The problem of non stationary data was overcomed applying the Smoothed Pseudo Wigner Villle (SPWV) time-frequency distribution. Spectral analysis was done before stress, during stress, immediately after stress and later in recovery. The spectral indices were calculated for both systolic blood pressure (SBP) and pulse interval (PI) series. The time evolution of spectral indices showed perturbed sympathovagal balance.

Spectral BRDF-based determination of proper measurement geometries to characterize color shift of special effect coatings.

PubMed

Ferrero, Alejandro; Rabal, Ana; Campos, Joaquín; Martínez-Verdú, Francisco; Chorro, Elísabet; Perales, Esther; Pons, Alicia; Hernanz, María Luisa

2013-02-01

A reduced set of measurement geometries allows the spectral reflectance of special effect coatings to be predicted for any other geometry. A physical model based on flake-related parameters has been used to determine nonredundant measurement geometries for the complete description of the spectral bidirectional reflectance distribution function (BRDF). The analysis of experimental spectral BRDF was carried out by means of principal component analysis. From this analysis, a set of nine measurement geometries was proposed to characterize special effect coatings. It was shown that, for two different special effect coatings, these geometries provide a good prediction of their complete color shift.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-05-25

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-11-23

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Spectral Electroencephalogram Analysis for the Evaluation of Encephalopathy Grade in Children With Acute Liver Failure.

PubMed

Press, Craig A; Morgan, Lindsey; Mills, Michele; Stack, Cynthia V; Goldstein, Joshua L; Alonso, Estella M; Wainwright, Mark S

2017-01-01

Spectral electroencephalogram analysis is a method for automated analysis of electroencephalogram patterns, which can be performed at the bedside. We sought to determine the utility of spectral electroencephalogram for grading hepatic encephalopathy in children with acute liver failure. Retrospective cohort study. Tertiary care pediatric hospital. Patients between 0 and 18 years old who presented with acute liver failure and were admitted to the PICU. None. Electroencephalograms were analyzed by spectral analysis including total power, relative δ, relative θ, relative α, relative β, θ-to-Δ ratio, and α-to-Δ ratio. Normal values and ranges were first derived using normal electroencephalograms from 70 children of 0-18 years old. Age had a significant effect on each variable measured (p < 0.03). Electroencephalograms from 33 patients with acute liver failure were available for spectral analysis. The median age was 4.3 years, 14 of 33 were male, and the majority had an indeterminate etiology of acute liver failure. Neuroimaging was performed in 26 cases and was normal in 20 cases (77%). The majority (64%) survived, and 82% had a good outcome with a score of 1-3 on the Pediatric Glasgow Outcome Scale-Extended at the time of discharge. Hepatic encephalopathy grade correlated with the qualitative visual electroencephalogram scores assigned by blinded neurophysiologists (rs = 0.493; p < 0.006). Spectral electroencephalogram characteristics varied significantly with the qualitative electroencephalogram classification (p < 0.05). Spectral electroencephalogram variables including relative Δ, relative θ, relative α, θ-to-Δ ratio, and α-to-Δ ratio all significantly varied with the qualitative electroencephalogram (p < 0.025). Moderate to severe hepatic encephalopathy was correlated with a total power of less than or equal to 50% of normal for children 0-3 years old, and with a relative θ of less than or equal to 50% normal for children more than 3 years old (p > 0.05). Spectral electroencephalogram classification correlated with outcome (p < 0.05). Spectral electroencephalogram analysis can be used to evaluate even young patients for hepatic encephalopathy and correlates with outcome. Spectral electroencephalogram may allow improved quantitative and reproducible assessment of hepatic encephalopathy grade in children with acute liver failure.

HEAO-1 analysis of Low Energy Detectors (LED)

NASA Technical Reports Server (NTRS)

Nousek, John A.

1992-01-01

The activities at Penn State University are described. During the period Oct. 1990 to Dec. 1991 work on HEAO-1 analysis of the Low Energy Detectors (LED) concentrated on using the improved detector spectral simulation model and fitting diffuse x-ray background spectral data. Spectral fitting results, x-ray point sources, and diffuse x-ray sources are described.

Single-hole spectral function and spin-charge separation in the t-J model

NASA Astrophysics Data System (ADS)

Mishchenko, A. S.; Prokof'ev, N. V.; Svistunov, B. V.

2001-07-01

Worm algorithm Monte Carlo simulations of the hole Green function with subsequent spectral analysis were performed for 0.1<=J/t<=0.4 on lattices with up to L×L=32×32 sites at a temperature as low as T=J/40, and present, apparently, the hole spectral function in the thermodynamic limit. Spectral analysis reveals a δ-function-sharp quasiparticle peak at the lower edge of the spectrum that is incompatible with the power-law singularity and thus rules out the possibility of spin-charge separation in this parameter range. Spectral continuum features two peaks separated by a gap ~4÷5 t.

Compact full-motion video hyperspectral cameras: development, image processing, and applications

NASA Astrophysics Data System (ADS)

Kanaev, A. V.

2015-10-01

Emergence of spectral pixel-level color filters has enabled development of hyper-spectral Full Motion Video (FMV) sensors operating in visible (EO) and infrared (IR) wavelengths. The new class of hyper-spectral cameras opens broad possibilities of its utilization for military and industry purposes. Indeed, such cameras are able to classify materials as well as detect and track spectral signatures continuously in real time while simultaneously providing an operator the benefit of enhanced-discrimination-color video. Supporting these extensive capabilities requires significant computational processing of the collected spectral data. In general, two processing streams are envisioned for mosaic array cameras. The first is spectral computation that provides essential spectral content analysis e.g. detection or classification. The second is presentation of the video to an operator that can offer the best display of the content depending on the performed task e.g. providing spatial resolution enhancement or color coding of the spectral analysis. These processing streams can be executed in parallel or they can utilize each other's results. The spectral analysis algorithms have been developed extensively, however demosaicking of more than three equally-sampled spectral bands has been explored scarcely. We present unique approach to demosaicking based on multi-band super-resolution and show the trade-off between spatial resolution and spectral content. Using imagery collected with developed 9-band SWIR camera we demonstrate several of its concepts of operation including detection and tracking. We also compare the demosaicking results to the results of multi-frame super-resolution as well as to the combined multi-frame and multiband processing.

Spectral identification of melon seeds variety based on k-nearest neighbor and Fisher discriminant analysis

NASA Astrophysics Data System (ADS)

Li, Cuiling; Jiang, Kai; Zhao, Xueguan; Fan, Pengfei; Wang, Xiu; Liu, Chuan

2017-10-01

Impurity of melon seeds variety will cause reductions of melon production and economic benefits of farmers, this research aimed to adopt spectral technology combined with chemometrics methods to identify melon seeds variety. Melon seeds whose varieties were "Yi Te Bai", "Yi Te Jin", "Jing Mi NO.7", "Jing Mi NO.11" and " Yi Li Sha Bai "were used as research samples. A simple spectral system was developed to collect reflective spectral data of melon seeds, including a light source unit, a spectral data acquisition unit and a data processing unit, the detection wavelength range of this system was 200-1100nm with spectral resolution of 0.14 7.7nm. The original reflective spectral data was pre-treated with de-trend (DT), multiple scattering correction (MSC), first derivative (FD), normalization (NOR) and Savitzky-Golay (SG) convolution smoothing methods. Principal Component Analysis (PCA) method was adopted to reduce the dimensions of reflective spectral data and extract principal components. K-nearest neighbour (KNN) and Fisher discriminant analysis (FDA) methods were used to develop discriminant models of melon seeds variety based on PCA. Spectral data pretreatments improved the discriminant effects of KNN and FDA, FDA generated better discriminant results than KNN, both KNN and FDA methods produced discriminant accuracies reaching to 90.0% for validation set. Research results showed that using spectral technology in combination with KNN and FDA modelling methods to identify melon seeds variety was feasible.

Examination of Spectral Transformations on Spectral Mixture Analysis

NASA Astrophysics Data System (ADS)

Deng, Y.; Wu, C.

2018-04-01

While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes' spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs' difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

Quantitative Doppler Analysis Using Conventional Color Flow Imaging Acquisitions.

PubMed

Karabiyik, Yucel; Ekroll, Ingvild Kinn; Eik-Nes, Sturla H; Lovstakken, Lasse

2018-05-01

Interleaved acquisitions used in conventional triplex mode result in a tradeoff between the frame rate and the quality of velocity estimates. On the other hand, workflow becomes inefficient when the user has to switch between different modes, and measurement variability is increased. This paper investigates the use of power spectral Capon estimator in quantitative Doppler analysis using data acquired with conventional color flow imaging (CFI) schemes. To preserve the number of samples used for velocity estimation, only spatial averaging was utilized, and clutter rejection was performed after spectral estimation. The resulting velocity spectra were evaluated in terms of spectral width using a recently proposed spectral envelope estimator. The spectral envelopes were also used for Doppler index calculations using in vivo and string phantom acquisitions. In vivo results demonstrated that the Capon estimator can provide spectral estimates with sufficient quality for quantitative analysis using packet-based CFI acquisitions. The calculated Doppler indices were similar to the values calculated using spectrograms estimated on a commercial ultrasound scanner.

Potential of FTIR spectroscopy for analysis of tears for diagnosis purposes.

PubMed

Travo, Adrian; Paya, Clément; Déléris, Gérard; Colin, Joseph; Mortemousque, Bruno; Forfar, Isabelle

2014-04-01

It has been widely reported that the tear film, which is crucially important as a protective barrier of the eye, undergoes biochemical changes as a result of a wide range of ocular pathology. This tends to suggest the possibility of early detection of ocular diseases on the basis of biochemical analysis of tears. However, studies of tears by conventional methods of biomolecular and biochemical analysis are often limited by methodological difficulties. Moreover, such analysis could not be applied in the clinic, where structural and morphological analyses by, mainly, slit-lamp biomicroscopy remains the recommended method. In this study, we assessed, for the first time, the potential of FTIR spectroscopy combined with advanced chemometric processing of spectral data for analysis of raw tears for diagnosis purposes. We first optimized sampling and spectral acquisition (tears collection method, tear sample volume, and preservation of the samples) for accurate spectral measurement. On the basis of the results, we focused our study on the possibility of discriminating tears from normal individuals from those of patients with different ocular pathologies, and showed that the most discriminating spectral range is that corresponding to variations of CH2 and CH3 of lipid aliphatic chains. We also report more subtle discrimination of tears from patients with keratoconus and those from patients with non-specific inflammatory ocular diseases, on the basis of variations in spectral ranges attributed notably to lipid and carbohydrate vibrations. Finally, we also succeeded in distinguishing tears from patients with early-stage and late-stage keratoconus on the basis of spectral features attributed to protein structure. Therefore, this study strongly suggests that FTIR spectral analysis of tears could be developed as a valuable and cost-saving tool for biochemical-based detection of ocular diseases, potentially before the appearance of the first morphological signs of diseases. Combined with supervised modelling methods and with use of a spectral data base acquired for representative patients, such a spectral approach could be a useful addition to current methods of clinical analysis for improvement of patient care.

Vibrations Detection in Industrial Pumps Based on Spectral Analysis to Increase Their Efficiency

NASA Astrophysics Data System (ADS)

Rachid, Belhadef; Hafaifa, Ahmed; Boumehraz, Mohamed

2016-03-01

Spectral analysis is the key tool for the study of vibration signals in rotating machinery. In this work, the vibration analysis applied for conditional preventive maintenance of such machines is proposed, as part of resolved problems related to vibration detection on the organs of these machines. The vibration signal of a centrifugal pump was treated to mount the benefits of the approach proposed. The obtained results present the signal estimation of a pump vibration using Fourier transform technique compared by the spectral analysis methods based on Prony approach.

Acoustic emission spectral analysis of fiber composite failure mechanisms

NASA Technical Reports Server (NTRS)

Egan, D. M.; Williams, J. H., Jr.

1978-01-01

The acoustic emission of graphite fiber polyimide composite failure mechanisms was investigated with emphasis on frequency spectrum analysis. Although visual examination of spectral densities could not distinguish among fracture sources, a paired-sample t statistical analysis of mean normalized spectral densities did provide quantitative discrimination among acoustic emissions from 10 deg, 90 deg, and plus or minus 45 deg, plus or minus 45 deg sub s specimens. Comparable discrimination was not obtained for 0 deg specimens.

Spectral and correlation analysis with applications to middle-atmosphere radars

NASA Technical Reports Server (NTRS)

Rastogi, Prabhat K.

1989-01-01

The correlation and spectral analysis methods for uniformly sampled stationary random signals, estimation of their spectral moments, and problems arising due to nonstationary are reviewed. Some of these methods are already in routine use in atmospheric radar experiments. Other methods based on the maximum entropy principle and time series models have been used in analyzing data, but are just beginning to receive attention in the analysis of radar signals. These methods are also briefly discussed.

Spectral signature verification using statistical analysis and text mining

NASA Astrophysics Data System (ADS)

DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.

2016-05-01

In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is present for comparison. The spectral validation method proposed is described from a practical application and analytical perspective.

Statistical Analysis of Spectral Properties and Prosodic Parameters of Emotional Speech

NASA Astrophysics Data System (ADS)

Přibil, J.; Přibilová, A.

2009-01-01

The paper addresses reflection of microintonation and spectral properties in male and female acted emotional speech. Microintonation component of speech melody is analyzed regarding its spectral and statistical parameters. According to psychological research of emotional speech, different emotions are accompanied by different spectral noise. We control its amount by spectral flatness according to which the high frequency noise is mixed in voiced frames during cepstral speech synthesis. Our experiments are aimed at statistical analysis of cepstral coefficient values and ranges of spectral flatness in three emotions (joy, sadness, anger), and a neutral state for comparison. Calculated histograms of spectral flatness distribution are visually compared and modelled by Gamma probability distribution. Histograms of cepstral coefficient distribution are evaluated and compared using skewness and kurtosis. Achieved statistical results show good correlation comparing male and female voices for all emotional states portrayed by several Czech and Slovak professional actors.

Random Initialisation of the Spectral Variables: an Alternate Approach for Initiating Multivariate Curve Resolution Alternating Least Square (MCR-ALS) Analysis.

PubMed

Kumar, Keshav

2017-11-01

Multivariate curve resolution alternating least square (MCR-ALS) analysis is the most commonly used curve resolution technique. The MCR-ALS model is fitted using the alternate least square (ALS) algorithm that needs initialisation of either contribution profiles or spectral profiles of each of the factor. The contribution profiles can be initialised using the evolve factor analysis; however, in principle, this approach requires that data must belong to the sequential process. The initialisation of the spectral profiles are usually carried out using the pure variable approach such as SIMPLISMA algorithm, this approach demands that each factor must have the pure variables in the data sets. Despite these limitations, the existing approaches have been quite a successful for initiating the MCR-ALS analysis. However, the present work proposes an alternate approach for the initialisation of the spectral variables by generating the random variables in the limits spanned by the maxima and minima of each spectral variable of the data set. The proposed approach does not require that there must be pure variables for each component of the multicomponent system or the concentration direction must follow the sequential process. The proposed approach is successfully validated using the excitation-emission matrix fluorescence data sets acquired for certain fluorophores with significant spectral overlap. The calculated contribution and spectral profiles of these fluorophores are found to correlate well with the experimental results. In summary, the present work proposes an alternate way to initiate the MCR-ALS analysis.

Fast Fourier Transform Spectral Analysis Program

NASA Technical Reports Server (NTRS)

Daniel, J. A., Jr.; Graves, M. L.; Hovey, N. M.

1969-01-01

Fast Fourier Transform Spectral Analysis Program is used in frequency spectrum analysis of postflight, space vehicle telemetered trajectory data. This computer program with a digital algorithm can calculate power spectrum rms amplitudes and cross spectrum of sampled parameters at even time increments.

Interactive Spectral Analysis and Computation (ISAAC)

NASA Technical Reports Server (NTRS)

Lytle, D. M.

1992-01-01

Isaac is a task in the NSO external package for IRAF. A descendant of a FORTRAN program written to analyze data from a Fourier transform spectrometer, the current implementation has been generalized sufficiently to make it useful for general spectral analysis and other one dimensional data analysis tasks. The user interface for Isaac is implemented as an interpreted mini-language containing a powerful, programmable vector calculator. Built-in commands provide much of the functionality needed to produce accurate line lists from input spectra. These built-in functions include automated spectral line finding, least squares fitting of Voigt profiles to spectral lines including equality constraints, various filters including an optimal filter construction tool, continuum fitting, and various I/O functions.

Program Package for the Analysis of High Resolution High Signal-To-Noise Stellar Spectra

NASA Astrophysics Data System (ADS)

Piskunov, N.; Ryabchikova, T.; Pakhomov, Yu.; Sitnova, T.; Alekseeva, S.; Mashonkina, L.; Nordlander, T.

2017-06-01

The program package SME (Spectroscopy Made Easy), designed to perform an analysis of stellar spectra using spectral fitting techniques, was updated due to adding new functions (isotopic and hyperfine splittins) in VALD and including grids of NLTE calculations for energy levels of few chemical elements. SME allows to derive automatically stellar atmospheric parameters: effective temperature, surface gravity, chemical abundances, radial and rotational velocities, turbulent velocities, taking into account all the effects defining spectral line formation. SME package uses the best grids of stellar atmospheres that allows us to perform spectral analysis with the similar accuracy in wide range of stellar parameters and metallicities - from dwarfs to giants of BAFGK spectral classes.

Signature extraction of ocean pollutants by eigenvector transformation of remote spectra

NASA Technical Reports Server (NTRS)

Grew, G. W.

1978-01-01

Spectral signatures of suspended matter in the ocean are being extracted through characteristic vector analysis of remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor). Spectral signatures appear to be obtainable through analyses of 'linear' clusters that appear on scatter diagrams associated with eigenvectors. Signatures associated with acid waste, sewage sludge, oil, and algae are presented. The application of vector analysis to two acid waste dumps overflown two years apart is examined in some detail. The relationships between eigenvectors and spectral signatures for these examples are analyzed. These cases demonstrate the value of characteristic vector analysis in remotely identifying pollutants in the ocean and in determining the consistency of their spectral signatures.

Spectral Phasor approach for fingerprinting of photo-activatable fluorescent proteins Dronpa, Kaede and KikGR

PubMed Central

Cutrale, Francesco; Salih, Anya; Gratton, Enrico

2013-01-01

The phasor global analysis algorithm is common for fluorescence lifetime applications, but has only been recently proposed for spectral analysis. Here the phasor representation and fingerprinting is exploited in its second harmonic to determine the number and spectra of photo-activated states as well as their conversion dynamics. We follow the sequence of photo-activation of proteins over time by rapidly collecting multiple spectral images. The phasor representation of the cumulative images provides easy identification of the spectral signatures of each photo-activatable protein. PMID:24040513

SpectralNET – an application for spectral graph analysis and visualization

PubMed Central

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-01-01

Background Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Results Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). Conclusion SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from . Source code is available upon request. PMID:16236170

SpectralNET--an application for spectral graph analysis and visualization.

PubMed

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-10-19

Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is available upon request.

UV spectroscopy including ISM line absorption: of the exciting star of Abell 35

NASA Astrophysics Data System (ADS)

Ziegler, M.; Rauch, T.; Werner, K.; Kruk, J. W.

Reliable spectral analysis that is based on high-resolution UV observations requires an adequate, simultaneous modeling of the interstellar line absorption and reddening. In the case of the central star of the planetary nebula Abell 35, BD-22 3467, we demonstrate our current standard spectral-analysis method that is based on the Tübingen NLTE Model-Atmosphere Package (TMAP). We present an on- going spectral analysis of FUSE and HST/STIS observations of BD-22 3467.

Laboratory spectroscopy of meteorite samples at UV-vis-NIR wavelengths: Analysis and discrimination by principal components analysis

NASA Astrophysics Data System (ADS)

Penttilä, Antti; Martikainen, Julia; Gritsevich, Maria; Muinonen, Karri

2018-02-01

Meteorite samples are measured with the University of Helsinki integrating-sphere UV-vis-NIR spectrometer. The resulting spectra of 30 meteorites are compared with selected spectra from the NASA Planetary Data System meteorite spectra database. The spectral measurements are transformed with the principal component analysis, and it is shown that different meteorite types can be distinguished from the transformed data. The motivation is to improve the link between asteroid spectral observations and meteorite spectral measurements.

Determining cantilever stiffness from thermal noise.

PubMed

Lübbe, Jannis; Temmen, Matthias; Rahe, Philipp; Kühnle, Angelika; Reichling, Michael

2013-01-01

We critically discuss the extraction of intrinsic cantilever properties, namely eigenfrequency f n , quality factor Q n and specifically the stiffness k n of the nth cantilever oscillation mode from thermal noise by an analysis of the power spectral density of displacement fluctuations of the cantilever in contact with a thermal bath. The practical applicability of this approach is demonstrated for several cantilevers with eigenfrequencies ranging from 50 kHz to 2 MHz. As such an analysis requires a sophisticated spectral analysis, we introduce a new method to determine k n from a spectral analysis of the demodulated oscillation signal of the excited cantilever that can be performed in the frequency range of 10 Hz to 1 kHz regardless of the eigenfrequency of the cantilever. We demonstrate that the latter method is in particular useful for noncontact atomic force microscopy (NC-AFM) where the required simple instrumentation for spectral analysis is available in most experimental systems.

Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis.

PubMed

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

2015-10-01

In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%.

Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis

PubMed Central

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

2015-01-01

In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%. PMID:26504638

Spatio-temporally resolved spectral measurements of laser-produced plasma and semiautomated spectral measurement-control and analysis software

NASA Astrophysics Data System (ADS)

Cao, S. Q.; Su, M. G.; Min, Q.; Sun, D. X.; O'Sullivan, G.; Dong, C. Z.

2018-02-01

A spatio-temporally resolved spectral measurement system of highly charged ions from laser-produced plasmas is presented. Corresponding semiautomated computer software for measurement control and spectral analysis has been written to achieve the best synchronicity possible among the instruments. This avoids the tedious comparative processes between experimental and theoretical results. To demonstrate the capabilities of this system, a series of spatio-temporally resolved experiments of laser-produced Al plasmas have been performed and applied to benchmark the software. The system is a useful tool for studying the spectral structures of highly charged ions and for evaluating the spatio-temporal evolution of laser-produced plasmas.

Spectral reconstruction analysis for enhancing signal-to-noise in time-resolved spectroscopies

NASA Astrophysics Data System (ADS)

Wilhelm, Michael J.; Smith, Jonathan M.; Dai, Hai-Lung

2015-09-01

We demonstrate a new spectral analysis for the enhancement of the signal-to-noise ratio (SNR) in time-resolved spectroscopies. Unlike the simple linear average which produces a single representative spectrum with enhanced SNR, this Spectral Reconstruction analysis (SRa) improves the SNR (by a factor of ca. 0 . 6 √{ n } ) for all n experimentally recorded time-resolved spectra. SRa operates by eliminating noise in the temporal domain, thereby attenuating noise in the spectral domain, as follows: Temporal profiles at each measured frequency are fit to a generic mathematical function that best represents the temporal evolution; spectra at each time are then reconstructed with data points from the fitted profiles. The SRa method is validated with simulated control spectral data sets. Finally, we apply SRa to two distinct experimentally measured sets of time-resolved IR emission spectra: (1) UV photolysis of carbonyl cyanide and (2) UV photolysis of vinyl cyanide.

Orbital forced frequencies in the 975000 year pollen record from Tenagi Philippon (Greece)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mommersteeg, H.J.P.M.; Young, R.; Wijmstra, T.A.

Frequency analysis was applied to different time series obtained from the 975 ka pollen record of Tenagi Philippon (Macedonia, Greece). These time series are characteristic of different vegetation types related to specific climatic conditions. Time control of the 196 m deep core was based on 11 finite {sup 14}C dates in the upper 17 m, magnetostratigraphy and correlation with the marine oxygen isotope stratigraphy. Maximum entropy spectrum analyses and thomson multi-taper spectrum analysis were applied using the complete time series. Periods of 95-99, 40-45. 24.0-25.5 and 19-21 ka which can be related to orbital forcing, as well as periods ofmore » about 68, 30 ka and of about 15.5, 13.5, 12 and 10.5 ka were detected. The detected periods of about 68, 30 ka and 16, 14, 12, 10.5 ka are likely to be harmonics and combination tones of the periods related to orbital forcing. The period of around 30 ka is possibly a secondary peak of obliquity. To study the stability of the detected periods through time, analysis with a moving window was employed. Signals in the eccentricity band were detected clearly during the last 650 ka. In the precession band, detected periods of about 24 ka show an increase in amplitude during the last 650 ka. The evolution of orbital frequencies during the last 1.0 Ma is in general agreement with the results of other marine and continental time series. Time series related to different climatic settings showed a different response to orbital forcing. Time series of vegetational elements sensitive to changes in net precipitation were forced in the precession and obliquity bands. Changes in precession caused changes in the monsoon system, which indirectly had a strong influence on the climatic history of Greece. Time series of vegetational elements which are more indicative of changes in annual temperature are forced in the eccentricity band. 54 refs., 12 figs., 3 tabs.« less

Antepartum Fetal Monitoring and Spectral Analysis of Preterm Birth Risk

NASA Astrophysics Data System (ADS)

Păsăricără, Alexandru; Nemescu, Dragoş; Arotăriţei, Dragoş; Rotariu, Cristian

2017-11-01

The monitoring and analysis of antepartum fetal and maternal recordings is a research area of notable interest due to the relatively high value of preterm birth. The interest stems from the improvement of devices used for monitoring. The current paper presents the spectral analysis of antepartum heart rate recordings conducted during a study in Romania at the Cuza Voda Obstetrics and Gynecology Clinical Hospital from Iasi between 2010 and 2014. The study focuses on normal and preterm birth risk subjects in order to determine differences between these two types or recordings in terms of spectral analysis.

Comparative Analysis of the Clinical Significance of Oscillatory Components in the Rhythmic Structure of Pulse Signal in the Diagnostics of Psychosomatic Disorders in School Age Children.

PubMed

Desova, A A; Dorofeyuk, A A; Anokhin, A M

2017-01-01

We performed a comparative analysis of the types of spectral density typical of various parameters of pulse signal. The experimental material was obtained during the examination of school age children with various psychosomatic disorders. We also performed a typological analysis of the spectral density functions corresponding to the time series of different parameters of a single oscillation of pulse signals; the results of their comparative analysis are presented. We determined the most significant spectral components for two disordersin children: arterial hypertension and mitral valve prolapse.

Atmospheric Properties Of T Dwarfs Inferred From Model Fits At Low Spectral Resolution

NASA Astrophysics Data System (ADS)

Giorla Godfrey, Paige A.; Rice, Emily L.; Filippazzo, Joseph C.; Douglas, Stephanie E.

2016-09-01

Brown dwarf spectral types (M, L, T, Y) correlate with spectral morphology, and generally appear to correspond with decreasing mass and effective temperature (Teff). Model fits to observed spectra suggest, however, that spectral subclasses do not share this monotonic temperature correlation, indicating that secondary parameters (gravity, metallicity, dust) significantly influence spectral morphology. We seekto disentangle the fundamental parameters that underlie the spectral type sequence of the coolest fully populated spectral class of brown dwarfs using atmosphere models. We investigate the relationship between spectral type and best fit model parameters for a sample of over 150 T dwarfs with low resolution (R 75-100) near-infrared ( 0.8-2.5 micron) SpeX Prism spectra. We use synthetic spectra from four model grids (Saumon & Marley 2008, Morley+ 2012, Saumon+ 2012, BT Settl 2013) and a Markov-Chain Monte Carlo (MCMC) analysis to determine robust best fit parameters and their uncertainties. We compare the consistency of each model grid by performing our analysis on the full spectrum and also on individual wavelength bands (Y,J,H,K). We find more consistent results between the J band and full spectrum fits and that our best fit spectral type-Teff results agree with the polynomial relationships of Stephens+2009 and Filippazzo+ 2015 using bolometric luminosities. Our analysis consists of the most extensive low resolution T dwarf model comparison to date, and lays the foundation for interpretation of cool brown dwarf and exoplanet spectra.

Comparative study of human blood Raman spectra and biochemical analysis of patients with cancer

NASA Astrophysics Data System (ADS)

Shamina, Lyudmila A.; Bratchenko, Ivan A.; Artemyev, Dmitry N.; Myakinin, Oleg O.; Moryatov, Alexander A.; Orlov, Andrey E.; Kozlov, Sergey V.; Zakharov, Valery P.

2018-04-01

In this study we measured spectral features of blood by Raman spectroscopy. Correlation of the obtained spectral data and biochemical studies results is investigated. Analysis of specific spectra allows for identification of informative spectral bands proportional to components whose content is associated with body fluids homeostasis changes at various pathological conditions. Regression analysis of the obtained spectral data allows for discriminating the lung cancer from other tumors with a posteriori probability of 88.3%. The potentiality of applying surface-enhanced Raman spectroscopy with utilized experimental setup for further studies of the body fluids component composition was estimated. The greatest signal amplification was achieved for the gold substrate with a surface roughness of 1 μm. In general, the developed approach of body fluids analysis provides the basis of a useful and minimally invasive method of pathologies screening.

Analysis of In-Situ Spectral Reflectance of Sago and Other Palms: Implications for Their Detection in Optical Satellite Images

NASA Astrophysics Data System (ADS)

Rendon Santillan, Jojene; Makinano-Santillan, Meriam

2018-04-01

We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa) to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345-1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2). Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

Studies on spectral analysis of randomly sampled signals: Application to laser velocimetry data

NASA Technical Reports Server (NTRS)

Sree, David

1992-01-01

Spectral analysis is very useful in determining the frequency characteristics of many turbulent flows, for example, vortex flows, tail buffeting, and other pulsating flows. It is also used for obtaining turbulence spectra from which the time and length scales associated with the turbulence structure can be estimated. These estimates, in turn, can be helpful for validation of theoretical/numerical flow turbulence models. Laser velocimetry (LV) is being extensively used in the experimental investigation of different types of flows, because of its inherent advantages; nonintrusive probing, high frequency response, no calibration requirements, etc. Typically, the output of an individual realization laser velocimeter is a set of randomly sampled velocity data. Spectral analysis of such data requires special techniques to obtain reliable estimates of correlation and power spectral density functions that describe the flow characteristics. FORTRAN codes for obtaining the autocorrelation and power spectral density estimates using the correlation-based slotting technique were developed. Extensive studies have been conducted on simulated first-order spectrum and sine signals to improve the spectral estimates. A first-order spectrum was chosen because it represents the characteristics of a typical one-dimensional turbulence spectrum. Digital prefiltering techniques, to improve the spectral estimates from randomly sampled data were applied. Studies show that the spectral estimates can be increased up to about five times the mean sampling rate.

Fractional-order Fourier analysis for ultrashort pulse characterization.

PubMed

Brunel, Marc; Coetmellec, Sébastien; Lelek, Mickael; Louradour, Frédéric

2007-06-01

We report what we believe to be the first experimental demonstration of ultrashort pulse characterization using fractional-order Fourier analysis. The analysis is applied to the interpretation of spectral interferometry resolved in time (SPIRIT) traces [which are spectral phase interferometry for direct electric field reconstruction (SPIDER)-like interferograms]. First, the fractional-order Fourier transformation is shown to naturally allow the determination of the cubic spectral phase coefficient of pulses to be analyzed. A simultaneous determination of both cubic and quadratic spectral phase coefficients of the pulses using the fractional-order Fourier series expansion is further demonstrated. This latter technique consists of localizing relative maxima in a 2D cartography representing decomposition coefficients. It is further used to reconstruct or filter SPIRIT traces.

Preliminary Geologic/spectral Analysis of LANDSAT-4 Thematic Mapper Data, Wind River/bighorn Basin Area, Wyoming

NASA Technical Reports Server (NTRS)

Lang, H. R.; Conel, J. E.; Paylor, E. D.

1984-01-01

A LIDQA evaluation for geologic applications of a LANDSAT TM scene covering the Wind River/Bighorn Basin area, Wyoming, is examined. This involves a quantitative assessment of data quality including spatial and spectral characteristics. Analysis is concentrated on the 6 visible, near infrared, and short wavelength infrared bands. Preliminary analysis demonstrates that: (1) principal component images derived from the correlation matrix provide the most useful geologic information. To extract surface spectral reflectance, the TM radiance data must be calibrated. Scatterplots demonstrate that TM data can be calibrated and sensor response is essentially linear. Low instrumental offset and gain settings result in spectral data that do not utilize the full dynamic range of the TM system.

A review of spectral methods

NASA Technical Reports Server (NTRS)

Lustman, L.

1984-01-01

An outline for spectral methods for partial differential equations is presented. The basic spectral algorithm is defined, collocation are emphasized and the main advantage of the method, the infinite order of accuracy in problems with smooth solutions are discussed. Examples of theoretical numerical analysis of spectral calculations are presented. An application of spectral methods to transonic flow is presented. The full potential transonic equation is among the best understood among nonlinear equations.

Comparative Analysis of Mass Spectral Similarity Measures on Peak Alignment for Comprehensive Two-Dimensional Gas Chromatography Mass Spectrometry

PubMed Central

2013-01-01

Peak alignment is a critical procedure in mass spectrometry-based biomarker discovery in metabolomics. One of peak alignment approaches to comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) data is peak matching-based alignment. A key to the peak matching-based alignment is the calculation of mass spectral similarity scores. Various mass spectral similarity measures have been developed mainly for compound identification, but the effect of these spectral similarity measures on the performance of peak matching-based alignment still remains unknown. Therefore, we selected five mass spectral similarity measures, cosine correlation, Pearson's correlation, Spearman's correlation, partial correlation, and part correlation, and examined their effects on peak alignment using two sets of experimental GC×GC-MS data. The results show that the spectral similarity measure does not affect the alignment accuracy significantly in analysis of data from less complex samples, while the partial correlation performs much better than other spectral similarity measures when analyzing experimental data acquired from complex biological samples. PMID:24151524

Spectral analysis of time series of categorical variables in earth sciences

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.; Dorador, Javier

2016-10-01

Time series of categorical variables often appear in Earth Science disciplines and there is considerable interest in studying their cyclic behavior. This is true, for example, when the type of facies, petrofabric features, ichnofabrics, fossil assemblages or mineral compositions are measured continuously over a core or throughout a stratigraphic succession. Here we deal with the problem of applying spectral analysis to such sequences. A full indicator approach is proposed to complement the spectral envelope often used in other disciplines. Additionally, a stand-alone computer program is provided for calculating the spectral envelope, in this case implementing the permutation test to assess the statistical significance of the spectral peaks. We studied simulated sequences as well as real data in order to illustrate the methodology.

Development of spectral analysis math models and software program and spectral analyzer, digital converter interface equipment design

NASA Technical Reports Server (NTRS)

Hayden, W. L.; Robinson, L. H.

1972-01-01

Spectral analyses of angle-modulated communication systems is studied by: (1) performing a literature survey of candidate power spectrum computational techniques, determining the computational requirements, and formulating a mathematical model satisfying these requirements; (2) implementing the model on UNIVAC 1230 digital computer as the Spectral Analysis Program (SAP); and (3) developing the hardware specifications for a data acquisition system which will acquire an input modulating signal for SAP. The SAP computational technique uses extended fast Fourier transform and represents a generalized approach for simple and complex modulating signals.

Spectral imaging toolbox: segmentation, hyperstack reconstruction, and batch processing of spectral images for the determination of cell and model membrane lipid order.

PubMed

Aron, Miles; Browning, Richard; Carugo, Dario; Sezgin, Erdinc; Bernardino de la Serna, Jorge; Eggeling, Christian; Stride, Eleanor

2017-05-12

Spectral imaging with polarity-sensitive fluorescent probes enables the quantification of cell and model membrane physical properties, including local hydration, fluidity, and lateral lipid packing, usually characterized by the generalized polarization (GP) parameter. With the development of commercial microscopes equipped with spectral detectors, spectral imaging has become a convenient and powerful technique for measuring GP and other membrane properties. The existing tools for spectral image processing, however, are insufficient for processing the large data sets afforded by this technological advancement, and are unsuitable for processing images acquired with rapidly internalized fluorescent probes. Here we present a MATLAB spectral imaging toolbox with the aim of overcoming these limitations. In addition to common operations, such as the calculation of distributions of GP values, generation of pseudo-colored GP maps, and spectral analysis, a key highlight of this tool is reliable membrane segmentation for probes that are rapidly internalized. Furthermore, handling for hyperstacks, 3D reconstruction and batch processing facilitates analysis of data sets generated by time series, z-stack, and area scan microscope operations. Finally, the object size distribution is determined, which can provide insight into the mechanisms underlying changes in membrane properties and is desirable for e.g. studies involving model membranes and surfactant coated particles. Analysis is demonstrated for cell membranes, cell-derived vesicles, model membranes, and microbubbles with environmentally-sensitive probes Laurdan, carboxyl-modified Laurdan (C-Laurdan), Di-4-ANEPPDHQ, and Di-4-AN(F)EPPTEA (FE), for quantification of the local lateral density of lipids or lipid packing. The Spectral Imaging Toolbox is a powerful tool for the segmentation and processing of large spectral imaging datasets with a reliable method for membrane segmentation and no ability in programming required. The Spectral Imaging Toolbox can be downloaded from https://uk.mathworks.com/matlabcentral/fileexchange/62617-spectral-imaging-toolbox .

Technical Training on High-Order Spectral Analysis and Thermal Anemometry Applications

NASA Technical Reports Server (NTRS)

Maslov, A. A.; Shiplyuk, A. N.; Sidirenko, A. A.; Bountin, D. A.

2003-01-01

The topics of thermal anemometry and high-order spectral analyses were the subject of the technical training. Specifically, the objective of the technical training was to study: (i) the recently introduced constant voltage anemometer (CVA) for high-speed boundary layer; and (ii) newly developed high-order spectral analysis techniques (HOSA). Both CVA and HOSA are relevant tools for studies of boundary layer transition and stability.

A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

PubMed

Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

2018-01-01

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An experiment with spectral analysis of emotional speech affected by orthodontic appliances

NASA Astrophysics Data System (ADS)

Přibil, Jiří; Přibilová, Anna; Ďuračková, Daniela

2012-11-01

The contribution describes the effect of the fixed and removable orthodontic appliances on spectral properties of emotional speech. Spectral changes were analyzed and evaluated by spectrograms and mean Welch’s periodograms. This alternative approach to the standard listening test enables to obtain objective comparison based on statistical analysis by ANOVA and hypothesis tests. Obtained results of analysis performed on short sentences of a female speaker in four emotional states (joyous, sad, angry, and neutral) show that, first of all, the removable orthodontic appliance affects the spectrograms of produced speech.

Mass Defect from Nuclear Physics to Mass Spectral Analysis.

PubMed

Pourshahian, Soheil

2017-09-01

Mass defect is associated with the binding energy of the nucleus. It is a fundamental property of the nucleus and the principle behind nuclear energy. Mass defect has also entered into the mass spectrometry terminology with the availability of high resolution mass spectrometry and has found application in mass spectral analysis. In this application, isobaric masses are differentiated and identified by their mass defect. What is the relationship between nuclear mass defect and mass defect used in mass spectral analysis, and are they the same? Graphical Abstract ᅟ.

Fusion of spectral models for dynamic modeling of sEMG and skeletal muscle force.

PubMed

Potluri, Chandrasekhar; Anugolu, Madhavi; Chiu, Steve; Urfer, Alex; Schoen, Marco P; Naidu, D Subbaram

2012-01-01

In this paper, we present a method of combining spectral models using a Kullback Information Criterion (KIC) data fusion algorithm. Surface Electromyographic (sEMG) signals and their corresponding skeletal muscle force signals are acquired from three sensors and pre-processed using a Half-Gaussian filter and a Chebyshev Type- II filter, respectively. Spectral models - Spectral Analysis (SPA), Empirical Transfer Function Estimate (ETFE), Spectral Analysis with Frequency Dependent Resolution (SPFRD) - are extracted from sEMG signals as input and skeletal muscle force as output signal. These signals are then employed in a System Identification (SI) routine to establish the dynamic models relating the input and output. After the individual models are extracted, the models are fused by a probability based KIC fusion algorithm. The results show that the SPFRD spectral models perform better than SPA and ETFE models in modeling the frequency content of the sEMG/skeletal muscle force data.

EXPLORING FUNCTIONAL CONNECTIVITY IN FMRI VIA CLUSTERING.

PubMed

Venkataraman, Archana; Van Dijk, Koene R A; Buckner, Randy L; Golland, Polina

2009-04-01

In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering algorithms as alternatives to the commonly used Seed-Based Analysis. To enable clustering of the entire brain volume, we use the Nyström Method to approximate the necessary spectral decompositions. We apply K-Means, Spectral Clustering and Seed-Based Analysis to resting-state fMRI data collected from 45 healthy young adults. Without placing any a priori constraints, both clustering methods yield partitions that are associated with brain systems previously identified via Seed-Based Analysis. Our empirical results suggest that clustering provides a valuable tool for functional connectivity analysis.

Novel full-spectral flow cytometry with multiple spectrally-adjacent fluorescent proteins and fluorochromes and visualization of in vivo cellular movement.

PubMed

Futamura, Koji; Sekino, Masashi; Hata, Akihiro; Ikebuchi, Ryoyo; Nakanishi, Yasutaka; Egawa, Gyohei; Kabashima, Kenji; Watanabe, Takeshi; Furuki, Motohiro; Tomura, Michio

2015-09-01

Flow cytometric analysis with multicolor fluoroprobes is an essential method for detecting biological signatures of cells. Here, we present a new full-spectral flow cytometer (spectral-FCM). Unlike conventional flow cytometer, this spectral-FCM acquires the emitted fluorescence for all probes across the full-spectrum from each cell with 32 channels sequential PMT unit after dispersion with prism, and extracts the signals of each fluoroprobe based on the spectral shape of each fluoroprobe using unique algorithm in high speed, high sensitive, accurate, automatic and real-time. The spectral-FCM detects the continuous changes in emission spectra from green to red of the photoconvertible protein, KikGR with high-spectral resolution and separates spectrally-adjacent fluoroprobes, such as FITC (Emission peak (Em) 519 nm) and EGFP (Em 507 nm). Moreover, the spectral-FCM can measure and subtract autofluorescence of each cell providing increased signal-to-noise ratios and improved resolution of dim samples, which leads to a transformative technology for investigation of single cell state and function. These advances make it possible to perform 11-color fluorescence analysis to visualize movement of multilinage immune cells by using KikGR-expressing mice. Thus, the novel spectral flow cytometry improves the combinational use of spectrally-adjacent various FPs and multicolor fluorochromes in metabolically active cell for the investigation of not only the immune system but also other research and clinical fields of use. © 2015 International Society for Advancement of Cytometry.

Use of Raman microscopy and band-target entropy minimization analysis to identify dyes in a commercial stamp. Implications for authentication and counterfeit detection.

PubMed

Widjaja, Effendi; Garland, Marc

2008-02-01

Raman microscopy was used in mapping mode to collect more than 1000 spectra in a 100 microm x 100 microm area from a commercial stamp. Band-target entropy minimization (BTEM) was then employed to unmix the mixture spectra in order to extract the pure component spectra of the samples. Three pure component spectral patterns with good signal-to-noise ratios were recovered, and their spatial distributions were determined. The three pure component spectral patterns were then identified as copper phthalocyanine blue, calcite-like material, and yellow organic dye material by comparison to known spectral libraries. The present investigation, consisting of (1) advanced curve resolution (blind-source separation) followed by (2) spectral data base matching, readily suggests extensions to authenticity and counterfeit studies of other types of commercial objects. The presence or absence of specific observable components form the basis for assessment. The present spectral analysis (BTEM) is applicable to highly overlapping spectral information. Since a priori information such as the number of components present and spectral libraries are not needed in BTEM, and since minor signals arising from trace components can be reconstructed, this analysis offers a robust approach to a wide variety of material problems involving authenticity and counterfeit issues.

Development of seismic fragility curves for low-rise masonry infilled reinforced concrete buildings by a coefficient-based method

NASA Astrophysics Data System (ADS)

Su, Ray Kai Leung; Lee, Chien-Liang

2013-06-01

This study presents a seismic fragility analysis and ultimate spectral displacement assessment of regular low-rise masonry infilled (MI) reinforced concrete (RC) buildings using a coefficient-based method. The coefficient-based method does not require a complicated finite element analysis; instead, it is a simplified procedure for assessing the spectral acceleration and displacement of buildings subjected to earthquakes. A regression analysis was first performed to obtain the best-fitting equations for the inter-story drift ratio (IDR) and period shift factor of low-rise MI RC buildings in response to the peak ground acceleration of earthquakes using published results obtained from shaking table tests. Both spectral acceleration- and spectral displacement-based fragility curves under various damage states (in terms of IDR) were then constructed using the coefficient-based method. Finally, the spectral displacements of low-rise MI RC buildings at the ultimate (or nearcollapse) state obtained from this paper and the literature were compared. The simulation results indicate that the fragility curves obtained from this study and other previous work correspond well. Furthermore, most of the spectral displacements of low-rise MI RC buildings at the ultimate state from the literature fall within the bounded spectral displacements predicted by the coefficient-based method.

The browning value changes and spectral analysis on the Maillard reaction product from glucose and methionine model system

NASA Astrophysics Data System (ADS)

Al-Baarri, A. N.; Legowo, A. M.; Widayat

2018-01-01

D-glucose has been understood to provide the various effect on the reactivity in Maillard reaction resulting in the changes in physical performance of food product. Therefore this research was done to analyse physical appearance of Maillard reaction product made of D-glucose and methionine as a model system. The changes in browning value and spectral analysis model system were determined. The glucose-methionine model system was produced through the heating treatment at 50°C and RH 70% for 24 hours. The data were collected for every three hour using spectrophotometer. As result, browning value was elevated with the increase of heating time and remarkably high if compare to the D-glucose only. Furthermore, the spectral analysis showed that methionine turned the pattern of peak appearance. As conclusion, methionine raised the browning value and changed the pattern of spectral analysis in Maillard reaction model system.

Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

2016-09-01

In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

Analysis of Vibration and Noise of Construction Machinery Based on Ensemble Empirical Mode Decomposition and Spectral Correlation Analysis Method

NASA Astrophysics Data System (ADS)

Chen, Yuebiao; Zhou, Yiqi; Yu, Gang; Lu, Dan

In order to analyze the effect of engine vibration on cab noise of construction machinery in multi-frequency bands, a new method based on ensemble empirical mode decomposition (EEMD) and spectral correlation analysis is proposed. Firstly, the intrinsic mode functions (IMFs) of vibration and noise signals were obtained by EEMD method, and then the IMFs which have the same frequency bands were selected. Secondly, we calculated the spectral correlation coefficients between the selected IMFs, getting the main frequency bands in which engine vibration has significant impact on cab noise. Thirdly, the dominated frequencies were picked out and analyzed by spectral analysis method. The study result shows that the main frequency bands and dominated frequencies in which engine vibration have serious impact on cab noise can be identified effectively by the proposed method, which provides effective guidance to noise reduction of construction machinery.

Objective determination of image end-members in spectral mixture analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Tompkins, Stefanie; Mustard, John F.; Pieters, Carle M.; Forsyth, Donald W.

1993-01-01

Spectral mixture analysis has been shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. Applications of AVIRIS data have ranged from mapping soils and bedrock to ecosystem studies. During the first phase of the approach, a set of end-members are selected from an image cube (image end-members) that best account for its spectral variance within a constrained, linear least squares mixing model. These image end-members are usually selected using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. We approach the problem of image end-member determination objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis.

PubMed

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-08-08

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis

PubMed Central

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-01-01

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases. PMID:28786947

Investigating cardiorespiratory interaction by cross-spectral analysis of event series

NASA Astrophysics Data System (ADS)

Schäfer, Carsten; Rosenblum, Michael G.; Pikovsky, Arkady S.; Kurths, Jürgen

2000-02-01

The human cardiovascular and respiratory systems interact with each other and show effects of modulation and synchronization. Here we present a cross-spectral technique that specifically considers the event-like character of the heartbeat and avoids typical restrictions of other spectral methods. Using models as well as experimental data, we demonstrate how modulation and synchronization can be distinguished. Finally, we compare the method to traditional techniques and to the analysis of instantaneous phases.

Turbulent Fluid Motion 5: Fourier Analysis, the Spectral Form of the Continuum Equations, and Homogeneous Turbulence

NASA Technical Reports Server (NTRS)

Deissler, Robert G.

1996-01-01

Background material on Fourier analysis and on the spectral form of the continuum equations, both averaged and unaveraged, are given. The equations are applied to a number of cases of homogeneous turbulence with and without mean gradients. Spectral transfer of turbulent activity between scales of motion is studied in some detail. The effects of mean shear, heat transfer, normal strain, and buoyancy are included in the analyses.

Tests of Spectral Cloud Classification Using DMSP Fine Mode Satellite Data.

DTIC Science & Technology

1980-06-02

processing techniques of potential value. Fourier spectral analysis was identified as the most promising technique to upgrade automated processing of...these measurements on the Earth’s surface is 0. 3 n mi. 3. Pickett, R.M., and Blackman, E.S. (1976) Automated Processing of Satellite Imagery Data at Air...and Pickett. R. Al. (1977) Automated Processing of Satellite Imagery Data at the Air Force Global Weather Central: Demonstrations of Spectral Analysis

Hyperthyroidism is characterized by both increased sympathetic and decreased vagal modulation of heart rate: evidence from spectral analysis of heart rate variability.

PubMed

Chen, Jin-Long; Chiu, Hung-Wen; Tseng, Yin-Jiun; Chu, Woei-Chyn

2006-06-01

The clinical manifestations of hyperthyroidism resemble those of the hyperadrenergic state. This study was designed to evaluate the impact of hyperthyroidism on the autonomic nervous system (ANS) and to investigate the relationship between serum thyroid hormone concentrations and parameters of spectral heart rate variability (HRV) analysis in hyperthyroidism. Thirty-two hyperthyroid Graves' disease patients (mean age 31 years) and 32 sex-, age-, and body mass index (BMI)-matched normal control subjects were recruited to receive one-channel electrocardiogram (ECG) recording. The cardiac autonomic nervous function was evaluated by the spectral analysis of HRV, which indicates the autonomic modulation of the sinus node. The correlation coefficients between serum thyroid hormone concentrations and parameters of the spectral HRV analysis were also computed. The hyperthyroid patients revealed significant differences (P < 0.001) compared with the controls in the following HRV parameters: a decrease in total power (TP), very low frequency power (VLF), low frequency power (LF), high frequency power (HF), and HF in normalized units (HF%); and an increase in LF in normalized units (LF%) and in the ratio of LF to HF (LF/HF). After correction of hyperthyroidism in 28 patients, all of the above parameters were restored to levels comparable to those of the controls. In addition, serum thyroid hormone concentrations showed significant correlations with spectral HRV parameters. Hyperthyroidism is in a sympathovagal imbalanced state, characterized by both increased sympathetic and decreased vagal modulation of the heart rate. These autonomic dysfunctions can be detected simultaneously by spectral analysis of HRV, and the spectral HRV parameters could reflect the disease severity in hyperthyroid patients.

Principal components analysis of Jupiter VIMS spectra

USGS Publications Warehouse

Bellucci, G.; Formisano, V.; D'Aversa, E.; Brown, R.H.; Baines, K.H.; Bibring, J.-P.; Buratti, B.J.; Capaccioni, F.; Cerroni, P.; Clark, R.N.; Coradini, A.; Cruikshank, D.P.; Drossart, P.; Jaumann, R.; Langevin, Y.; Matson, D.L.; McCord, T.B.; Mennella, V.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Chamberlain, M.C.; Hansen, G.; Hibbits, K.; Showalter, M.; Filacchione, G.

2004-01-01

During Cassini - Jupiter flyby occurred in December 2000, Visual-Infrared mapping spectrometer (VIMS) instrument took several image cubes of Jupiter at different phase angles and distances. We have analysed the spectral images acquired by the VIMS visual channel by means of a principal component analysis technique (PCA). The original data set consists of 96 spectral images in the 0.35-1.05 ??m wavelength range. The product of the analysis are new PC bands, which contain all the spectral variance of the original data. These new components have been used to produce a map of Jupiter made of seven coherent spectral classes. The map confirms previously published work done on the Great Red Spot by using NIMS data. Some other new findings, presently under investigation, are presented. ?? 2004 Published by Elsevier Ltd on behalf of COSPAR.

Proton exchange membrane fuel cell diagnosis by spectral characterization of the electrochemical noise

NASA Astrophysics Data System (ADS)

Maizia, R.; Dib, A.; Thomas, A.; Martemianov, S.

2017-02-01

Electrochemical noise analysis (ENA) has been performed for the diagnosis of proton-exchange membrane fuel cell (PEMFC) under various operating conditions. Its interest is related with the possibility of a non-invasive on-line diagnosis of a commercial fuel cell. A methodology of spectral analysis has been developed and an evaluation of the stationarity of the signal has been proposed. It has been revealed that the spectral signature of fuel cell, is a linear slope with a fractional power dependence 1/fα where α = 2 for different relative humidities and current densities. Experimental results reveal that the electrochemical noise is sensitive to the water management, especially under dry conditions. At RHH2 = 20% and RHair = 20%, spectral analysis shows a three linear slopes signature on the spectrum at low frequency range (f < 100 Hz). This results indicates that power spectral density, calculated thanks to FFT, can be used for the detection of an incorrect fuel cell water balance.

Detection of hidden mineral deposits by airborne spectral analysis of forest canopies. [Spirit Lake, Washington; Catheart Mountain, Maine; Blacktail Mountain, Montana; and Cotter Basin, Montana

NASA Technical Reports Server (NTRS)

Collins, W.; Chang, S. H.; Kuo, J. T.

1984-01-01

Data from field surveys and biogeochemical tests conducted in Maine, Montana, and Washington strongly correlate with results obtained using high resolution airborne spectroradiometer which detects an anomalous spectral waveform that appears definitely associated with sulfide mineralization. The spectral region most affected by mineral stress is between 550 nm and 750 nm. Spectral variations observed in the field occur on the wings of the red chlorophyll band centered at about 690 nm. The metal-stress-induced variations on the absorption band wing are most successfully resolved in the high spectral resolution field data using a waveform analysis technique. The development of chlorophyll pigments was retarded in greenhouse plants doped with copper and zinc in the laboratory. The lowered chlorophyll production resulted in changes on the wings of the chlorophyll bands of reflectance spectra of the plants. The airborne spectroradiometer system and waveform analysis remains the most sensitive technique for biogeochemical surveys.

Software algorithm and hardware design for real-time implementation of new spectral estimator

PubMed Central

2014-01-01

Background Real-time spectral analyzers can be difficult to implement for PC computer-based systems because of the potential for high computational cost, and algorithm complexity. In this work a new spectral estimator (NSE) is developed for real-time analysis, and compared with the discrete Fourier transform (DFT). Method Clinical data in the form of 216 fractionated atrial electrogram sequences were used as inputs. The sample rate for acquisition was 977 Hz, or approximately 1 millisecond between digital samples. Real-time NSE power spectra were generated for 16,384 consecutive data points. The same data sequences were used for spectral calculation using a radix-2 implementation of the DFT. The NSE algorithm was also developed for implementation as a real-time spectral analyzer electronic circuit board. Results The average interval for a single real-time spectral calculation in software was 3.29 μs for NSE versus 504.5 μs for DFT. Thus for real-time spectral analysis, the NSE algorithm is approximately 150× faster than the DFT. Over a 1 millisecond sampling period, the NSE algorithm had the capability to spectrally analyze a maximum of 303 data channels, while the DFT algorithm could only analyze a single channel. Moreover, for the 8 second sequences, the NSE spectral resolution in the 3-12 Hz range was 0.037 Hz while the DFT spectral resolution was only 0.122 Hz. The NSE was also found to be implementable as a standalone spectral analyzer board using approximately 26 integrated circuits at a cost of approximately $500. The software files used for analysis are included as a supplement, please see the Additional files 1 and 2. Conclusions The NSE real-time algorithm has low computational cost and complexity, and is implementable in both software and hardware for 1 millisecond updates of multichannel spectra. The algorithm may be helpful to guide radiofrequency catheter ablation in real time. PMID:24886214

Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice and snow, and other materials: The USGS tricorder algorithm

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.

1995-01-01

One of the challenges of Imaging Spectroscopy is the identification, mapping and abundance determination of materials, whether mineral, vegetable, or liquid, given enough spectral range, spectral resolution, signal to noise, and spatial resolution. Many materials show diagnostic absorption features in the visual and near infrared region (0.4 to 2.5 micrometers) of the spectrum. This region is covered by the modern imaging spectrometers such as AVIRIS. The challenge is to identify the materials from absorption bands in their spectra, and determine what specific analyses must be done to derive particular parameters of interest, ranging from simply identifying its presence to deriving its abundance, or determining specific chemistry of the material. Recently, a new analysis algorithm was developed that uses a digital spectral library of known materials and a fast, modified-least-squares method of determining if a single spectral feature for a given material is present. Clark et al. made another advance in the mapping algorithm: simultaneously mapping multiple minerals using multiple spectral features. This was done by a modified-least-squares fit of spectral features, from data in a digital spectral library, to corresponding spectral features in the image data. This version has now been superseded by a more comprehensive spectral analysis system called Tricorder.

Spectral characteristics of Shuttle glow

NASA Technical Reports Server (NTRS)

Viereck, R. A.; Mende, S. B.; Murad, E.; Swenson, G. R.; Pike, C. P.; Culbertson, F. L.; Springer, R. C.

1992-01-01

The glowing cloud near the ram surfaces of the Space Shuttle was observed with a hand-held, intensified spectrograph operated by the astronauts from the aft-flight-deck of the Space Shuttle. The spectral measurements were made between 400 and 800 nm with a resolution of 3 nm. Analysis of the spectral response of the instrument and the transmission of the Shuttle window was performed on orbit using earth-airglow OH Meinel bands. This analysis resulted in a correction of the Shuttle glow intensity in the spectral region between 700 and 800 nm. The data presented in this report is in better agreement with laboratory measurements of the NO2 continuum.

Demodulation circuit for AC motor current spectral analysis

DOEpatents

Hendrix, Donald E.; Smith, Stephen F.

1990-12-18

A motor current analysis method for the remote, noninvasive inspection of electric motor-operated systems. Synchronous amplitude demodulation and phase demodulation circuits are used singly and in combination along with a frequency analyzer to produce improved spectral analysis of load-induced frequencies present in the electric current flowing in a motor-driven system.

Spectral analysis of the Crab Nebula and GRB 160530A with the Compton Spectrometer and Imager

NASA Astrophysics Data System (ADS)

Sleator, Clio; Boggs, Steven E.; Chiu, Jeng-Lun; Kierans, Carolyn; Lowell, Alexander; Tomsick, John; Zoglauer, Andreas; Amman, Mark; Chang, Hsiang-Kuang; Tseng, Chao-Hsiung; Yang, Chien-Ying; Lin, Chih H.; Jean, Pierre; von Ballmoos, Peter

2017-08-01

The Compton Spectrometer and Imager (COSI) is a balloon-borne soft gamma-ray (0.2-5 MeV) telescope designed to study astrophysical sources including gamma-ray bursts and compact objects. As a compact Compton telescope, COSI has inherent sensitivity to polarization. COSI utilizes 12 germanium detectors to provide excellent spectral resolution. On May 17, 2016, COSI was launched from Wanaka, New Zealand and completed a successful 46-day flight on NASA’s new Superpressure balloon. To perform spectral analysis with COSI, we have developed an accurate instrument model as required for the response matrix. With carefully chosen background regions, we are able to fit the background-subtracted spectra in XSPEC. We have developed a model of the atmosphere above COSI based on the NRLMSISE-00 Atmosphere Model to include in our spectral fits. The Crab and GRB 160530A are among the sources detected during the 2016 flight. We present spectral analysis of these two point sources. Our GRB 160530A results are consistent with those from other instruments, confirming COSI’s spectral abilities. Furthermore, we discuss prospects for measuring the Crab polarization with COSI.

Using foreground/background analysis to determine leaf and canopy chemistry

NASA Technical Reports Server (NTRS)

Pinzon, J. E.; Ustin, S. L.; Hart, Q. J.; Jacquemoud, S.; Smith, M. O.

1995-01-01

Spectral Mixture Analysis (SMA) has become a well established procedure for analyzing imaging spectrometry data, however, the technique is relatively insensitive to minor sources of spectral variation (e.g., discriminating stressed from unstressed vegetation and variations in canopy chemistry). Other statistical approaches have been tried e.g., stepwise multiple linear regression analysis to predict canopy chemistry. Grossman et al. reported that SMLR is sensitive to measurement error and that the prediction of minor chemical components are not independent of patterns observed in more dominant spectral components like water. Further, they observed that the relationships were strongly dependent on the mode of expressing reflectance (R, -log R) and whether chemistry was expressed on a weight (g/g) or are basis (g/sq m). Thus, alternative multivariate techniques need to be examined. Smith et al. reported a revised SMA that they termed Foreground/Background Analysis (FBA) that permits directing the analysis along any axis of variance by identifying vectors through the n-dimensional spectral volume orthonormal to each other. Here, we report an application of the FBA technique for the detection of canopy chemistry using a modified form of the analysis.

Spectral analysis comparisons of Fourier-theory-based methods and minimum variance (Capon) methods

NASA Astrophysics Data System (ADS)

Garbanzo-Salas, Marcial; Hocking, Wayne. K.

2015-09-01

In recent years, adaptive (data dependent) methods have been introduced into many areas where Fourier spectral analysis has traditionally been used. Although the data-dependent methods are often advanced as being superior to Fourier methods, they do require some finesse in choosing the order of the relevant filters. In performing comparisons, we have found some concerns about the mappings, particularly when related to cases involving many spectral lines or even continuous spectral signals. Using numerical simulations, several comparisons between Fourier transform procedures and minimum variance method (MVM) have been performed. For multiple frequency signals, the MVM resolves most of the frequency content only for filters that have more degrees of freedom than the number of distinct spectral lines in the signal. In the case of Gaussian spectral approximation, MVM will always underestimate the width, and can misappropriate the location of spectral line in some circumstances. Large filters can be used to improve results with multiple frequency signals, but are computationally inefficient. Significant biases can occur when using MVM to study spectral information or echo power from the atmosphere. Artifacts and artificial narrowing of turbulent layers is one such impact.

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

2003-01-01

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Spectral characterization of the LANDSAT thematic mapper sensors

NASA Technical Reports Server (NTRS)

Markham, B. L.; Barker, J. L.

1983-01-01

Data collected on the spectral characteristics of the LANDSAT-4 and LANDSAT-4 backup thematic mapper instruments, the protoflight (TM/PF) and flight (TM/F) models, respectively, are presented and analyzed. Tests were conducted on the instruments and their components to determine compliance with two sets of spectral specifications: band-by-band spectral coverage and channel-by-channel within-band spectral matching. Spectral coverage specifications were placed on: (1) band edges--points at 50% of peak response, (2) band edge slopes--steepness of rise and fall-off of response, (3) spectral flatness--evenness of response between edges, and (4) spurious system response--ratio of out-of-band response to in-band response. Compliance with the spectral coverage specifications was determined by analysis of spectral measurements on the individual components contributing to the overall spectral response: filters, detectors, and optical surfaces.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

A solar radio dynamic spectrograph with flexible temporal-spectral resolution

NASA Astrophysics Data System (ADS)

Du, Qing-Fu; Chen, Lei; Zhao, Yue-Chang; Li, Xin; Zhou, Yan; Zhang, Jun-Rui; Yan, Fa-Bao; Feng, Shi-Wei; Li, Chuan-Yang; Chen, Yao

2017-09-01

Observation and research on solar radio emission have unique scientific values in solar and space physics and related space weather forecasting applications, since the observed spectral structures may carry important information about energetic electrons and underlying physical mechanisms. In this study, we present the design of a novel dynamic spectrograph that has been installed at the Chashan Solar Radio Observatory operated by the Laboratory for Radio Technologies, Institute of Space Sciences at Shandong University. The spectrograph is characterized by real-time storage of digitized radio intensity data in the time domain and its capability to perform off-line spectral analysis of the radio spectra. The analog signals received via antennas and amplified with a low-noise amplifier are converted into digital data at a speed reaching up to 32 k data points per millisecond. The digital data are then saved into a high-speed electronic disk for further off-line spectral analysis. Using different word lengths (1-32 k) and time cadences (5 ms-10 s) for off-line fast Fourier transform analysis, we can obtain the dynamic spectrum of a radio burst with different (user-defined) temporal (5 ms-10 s) and spectral (3 kHz˜320 kHz) resolutions. This enables great flexibility and convenience in data analysis of solar radio bursts, especially when some specific fine spectral structures are under study.

Quantitative Analysis of Spectral Interference of Spontaneous Raman Scattering in High-Pressure Fuel-Rich H2-Air Combustion

NASA Technical Reports Server (NTRS)

Kojima, Jun; Nguyen, Quang-Viet

2004-01-01

We present a theoretical study of the spectral interferences in the spontaneous Raman scattering spectra of major combustion products in 30-atm fuel-rich hydrogen-air flames. An effective methodology is introduced to choose an appropriate line-shape model for simulating Raman spectra in high-pressure combustion environments. The Voigt profile with the additive approximation assumption was found to provide a reasonable model of the spectral line shape for the present analysis. The rotational/vibrational Raman spectra of H2, N2, and H2O were calculated using an anharmonic-oscillator model using the latest collisional broadening coefficients. The calculated spectra were validated with data obtained in a 10-atm fuel-rich H2-air flame and showed excellent agreement. Our quantitative spectral analysis for equivalence ratios ranging from 1.5 to 5.0 revealed substantial amounts of spectral cross-talk between the rotational H2 lines and the N2 O-/Q-branch; and between the vibrational H2O(0,3) line and the vibrational H2O spectrum. We also address the temperature dependence of the spectral cross-talk and extend our analysis to include a cross-talk compensation technique that removes the nterference arising from the H2 Raman spectra onto the N2, or H2O spectra.

Biologically-inspired data decorrelation for hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Picon, Artzai; Ghita, Ovidiu; Rodriguez-Vaamonde, Sergio; Iriondo, Pedro Ma; Whelan, Paul F.

2011-12-01

Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors) is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA), linear discriminant analysis (LDA), wavelet decomposition (WD), or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral) characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

[Review of digital ground object spectral library].

PubMed

Zhou, Xiao-Hu; Zhou, Ding-Wu

2009-06-01

A higher spectral resolution is the main direction of developing remote sensing technology, and it is quite important to set up the digital ground object reflectance spectral database library, one of fundamental research fields in remote sensing application. Remote sensing application has been increasingly relying on ground object spectral characteristics, and quantitative analysis has been developed to a new stage. The present article summarized and systematically introduced the research status quo and development trend of digital ground object reflectance spectral libraries at home and in the world in recent years. Introducing the spectral libraries has been established, including desertification spectral database library, plants spectral database library, geological spectral database library, soil spectral database library, minerals spectral database library, cloud spectral database library, snow spectral database library, the atmosphere spectral database library, rocks spectral database library, water spectral database library, meteorites spectral database library, moon rock spectral database library, and man-made materials spectral database library, mixture spectral database library, volatile compounds spectral database library, and liquids spectral database library. In the process of establishing spectral database libraries, there have been some problems, such as the lack of uniform national spectral database standard and uniform standards for the ground object features as well as the comparability between different databases. In addition, data sharing mechanism can not be carried out, etc. This article also put forward some suggestions on those problems.

ACCURATE CHARACTERIZATION OF HIGH-DEGREE MODES USING MDI OBSERVATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Korzennik, S. G.; Rabello-Soares, M. C.; Schou, J.

2013-08-01

We present the first accurate characterization of high-degree modes, derived using the best Michelson Doppler Imager (MDI) full-disk full-resolution data set available. A 90 day long time series of full-disk 2 arcsec pixel{sup -1} resolution Dopplergrams was acquired in 2001, thanks to the high rate telemetry provided by the Deep Space Network. These Dopplergrams were spatially decomposed using our best estimate of the image scale and the known components of MDI's image distortion. A multi-taper power spectrum estimator was used to generate power spectra for all degrees and all azimuthal orders, up to l = 1000. We used a largemore » number of tapers to reduce the realization noise, since at high degrees the individual modes blend into ridges and thus there is no reason to preserve a high spectral resolution. These power spectra were fitted for all degrees and all azimuthal orders, between l = 100 and l = 1000, and for all the orders with substantial amplitude. This fitting generated in excess of 5.2 Multiplication-Sign 10{sup 6} individual estimates of ridge frequencies, line widths, amplitudes, and asymmetries (singlets), corresponding to some 5700 multiplets (l, n). Fitting at high degrees generates ridge characteristics, characteristics that do not correspond to the underlying mode characteristics. We used a sophisticated forward modeling to recover the best possible estimate of the underlying mode characteristics (mode frequencies, as well as line widths, amplitudes, and asymmetries). We describe in detail this modeling and its validation. The modeling has been extensively reviewed and refined, by including an iterative process to improve its input parameters to better match the observations. Also, the contribution of the leakage matrix on the accuracy of the procedure has been carefully assessed. We present the derived set of corrected mode characteristics, which includes not only frequencies, but line widths, asymmetries, and amplitudes. We present and discuss their uncertainties and the precision of the ridge-to-mode correction schemes, through a detailed assessment of the sensitivity of the model to its input set. The precision of the ridge-to-mode correction is indicative of any possible residual systematic biases in the inferred mode characteristics. In our conclusions, we address how to further improve these estimates, and the implications for other data sets, like GONG+ and HMI.« less

Multi range spectral feature fitting for hyperspectral imagery in extracting oilseed rape planting area

NASA Astrophysics Data System (ADS)

Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

2013-12-01

Spectral feature fitting (SFF) is a commonly used strategy for hyperspectral imagery analysis to discriminate ground targets. Compared to other image analysis techniques, SFF does not secure higher accuracy in extracting image information in all circumstances. Multi range spectral feature fitting (MRSFF) from ENVI software allows user to focus on those interesting spectral features to yield better performance. Thus spectral wavelength ranges and their corresponding weights must be determined. The purpose of this article is to demonstrate the performance of MRSFF in oilseed rape planting area extraction. A practical method for defining the weighted values, the variance coefficient weight method, was proposed to set up criterion. Oilseed rape field canopy spectra from the whole growth stage were collected prior to investigating its phenological varieties; oilseed rape endmember spectra were extracted from the Hyperion image as identifying samples to be used in analyzing the oilseed rape field. Wavelength range divisions were determined by the difference between field-measured spectra and image spectra, and image spectral variance coefficient weights for each wavelength range were calculated corresponding to field-measured spectra from the closest date. By using MRSFF, wavelength ranges were classified to characterize the target's spectral features without compromising spectral profile's entirety. The analysis was substantially successful in extracting oilseed rape planting areas (RMSE ≤ 0.06), and the RMSE histogram indicated a superior result compared to a conventional SFF. Accuracy assessment was based on the mapping result compared with spectral angle mapping (SAM) and the normalized difference vegetation index (NDVI). The MRSFF yielded a robust, convincible result and, therefore, may further the use of hyperspectral imagery in precision agriculture.

Spectral and geometrical variation of the bidirectional reflectance distribution function of diffuse reflectance standards.

PubMed

Ferrero, Alejandro; Rabal, Ana María; Campos, Joaquín; Pons, Alicia; Hernanz, María Luisa

2012-12-20

A study on the variation of the spectral bidirectional reflectance distribution function (BRDF) of four diffuse reflectance standards (matte ceramic, BaSO(4), Spectralon, and white Russian opal glass) is accomplished through this work. Spectral BRDF measurements were carried out and, using principal components analysis, its spectral and geometrical variation respect to a reference geometry was assessed from the experimental data. Several descriptors were defined in order to compare the spectral BRDF variation of the four materials.

Real-time spectral analysis of HRV signals: an interactive and user-friendly PC system.

PubMed

Basano, L; Canepa, F; Ottonello, P

1998-01-01

We present a real-time system, built around a PC and a low-cost data acquisition board, for the spectral analysis of the heart rate variability signal. The Windows-like operating environment on which it is based makes the computer program very user-friendly even for non-specialized personnel. The Power Spectral Density is computed through the use of a hybrid method, in which a classical FFT analysis follows an autoregressive finite-extension of data; the stationarity of the sequence is continuously checked. The use of this algorithm gives a high degree of robustness of the spectral estimation. Moreover, always in real time, the FFT of every data block is computed and displayed in order to corroborate the results as well as to allow the user to interactively choose a proper AR model order.

Feasibility study of a novel miniaturized spectral imaging system architecture in UAV surveillance

NASA Astrophysics Data System (ADS)

Liu, Shuyang; Zhou, Tao; Jia, Xiaodong; Cui, Hushan; Huang, Chengjun

2016-01-01

The spectral imaging technology is able to analysis the spectral and spatial geometric character of the target at the same time. To break through the limitation brought by the size, weight and cost of the traditional spectral imaging instrument, a miniaturized novel spectral imaging based on CMOS processing has been introduced in the market. This technology has enabled the possibility of applying spectral imaging in the UAV platform. In this paper, the relevant technology and the related possible applications have been presented to implement a quick, flexible and more detailed remote sensing system.

Spectrum Analyzers Incorporating Tunable WGM Resonators

NASA Technical Reports Server (NTRS)

Savchenkov, Anatoliy; Matsko, Andrey; Strekalov, Dmitry; Maleki, Lute

2009-01-01

A photonic instrument is proposed to boost the resolution for ultraviolet/ optical/infrared spectral analysis and spectral imaging allowing the detection of narrow (0.00007-to-0.07-picometer wavelength resolution range) optical spectral signatures of chemical elements in space and planetary atmospheres. The idea underlying the proposal is to exploit the advantageous spectral characteristics of whispering-gallery-mode (WGM) resonators to obtain spectral resolutions at least three orders of magnitude greater than those of optical spectrum analyzers now in use. Such high resolutions would enable measurement of spectral features that could not be resolved by prior instruments.

Spectral reflectance properties (0.4-2.5 μm) of secondary Fe-oxide, Fe-hydroxide, and Fe-sulphate-hydrate minerals associated with sulphide-bearing mine wastes

USGS Publications Warehouse

Crowley, J.K.; Williams, D.E.; Hammarstrom, J.M.; Piatak, N.; Chou, I.-Ming; Mars, J.C.

2003-01-01

Diffuse reflectance spectra of 15 mineral species commonly associated with sulphide-bearing mine wastes show diagnostic absorption bands related to electronic processes involving ferric and/or ferrous iron, and to vibrational processes involving water and hydroxyl. Many of these absorption bands are relatively broad and overlapping; however, spectral analysis methods, including continuum removal and derivative analysis, permit most of the minerals to be distinguished. Key spectral differences between the minerals are illustrated in a series of plots showing major absorption band centres and other spectral feature positions. Because secondary iron minerals are sensitive indicators of pH, Eh, relative humidity, and other environmental conditions, spectral mapping of mineral distributions promises to have important application to mine waste remediation studies.

Multispectral scanner system parameter study and analysis software system description, volume 2

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator); Mobasseri, B. G.; Wiersma, D. J.; Wiswell, E. R.; Mcgillem, C. D.; Anuta, P. E.

1978-01-01

The author has identified the following significant results. The integration of the available methods provided the analyst with the unified scanner analysis package (USAP), the flexibility and versatility of which was superior to many previous integrated techniques. The USAP consisted of three main subsystems; (1) a spatial path, (2) a spectral path, and (3) a set of analytic classification accuracy estimators which evaluated the system performance. The spatial path consisted of satellite and/or aircraft data, data correlation analyzer, scanner IFOV, and random noise model. The output of the spatial path was fed into the analytic classification and accuracy predictor. The spectral path consisted of laboratory and/or field spectral data, EXOSYS data retrieval, optimum spectral function calculation, data transformation, and statistics calculation. The output of the spectral path was fended into the stratified posterior performance estimator.

Signal-to-noise contribution of principal component loads in reconstructed near-infrared Raman tissue spectra.

PubMed

Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R

2010-01-01

The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can reliably be used in the low SNR data set (set B) compared to the high SNR data set (set A). Despite the fact that no definitive threshold could be found, this method may help to determine the cutoff for the number of principal components used in discriminant analysis. Future analysis of a selection of spectral databases using this technique will allow optimum thresholds to be selected for different applications and spectral data quality levels.

On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Huang; Peng, Chung Kang;

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

PubMed Central

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities. PMID:26953180

Ratiometric spectral imaging for fast tumor detection and chemotherapy monitoring in vivo

PubMed Central

Hwang, Jae Youn; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

2011-01-01

We report a novel in vivo spectral imaging approach to cancer detection and chemotherapy assessment. We describe and characterize a ratiometric spectral imaging and analysis method and evaluate its performance for tumor detection and delineation by quantitatively monitoring the specific accumulation of targeted gallium corrole (HerGa) into HER2-positive (HER2 +) breast tumors. HerGa temporal accumulation in nude mice bearing HER2 + breast tumors was monitored comparatively by a. this new ratiometric imaging and analysis method; b. established (reflectance and fluorescence) spectral imaging; c. more commonly used fluorescence intensity imaging. We also tested the feasibility of HerGa imaging in vivo using the ratiometric spectral imaging method for tumor detection and delineation. Our results show that the new method not only provides better quantitative information than typical spectral imaging, but also better specificity than standard fluorescence intensity imaging, thus allowing enhanced in vivo outlining of tumors and dynamic, quantitative monitoring of targeted chemotherapy agent accumulation into them. PMID:21721808

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Novel Multidimensional Cross-Correlation Data Comparison Techniques for Spectroscopic Discernment in a Volumetrically Sensitive, Moderating Type Neutron Spectrometer

NASA Astrophysics Data System (ADS)

Hoshor, Cory; Young, Stephan; Rogers, Brent; Currie, James; Oakes, Thomas; Scott, Paul; Miller, William; Caruso, Anthony

2014-03-01

A novel application of the Pearson Cross-Correlation to neutron spectral discernment in a moderating type neutron spectrometer is introduced. This cross-correlation analysis will be applied to spectral response data collected through both MCNP simulation and empirical measurement by the volumetrically sensitive spectrometer for comparison in 1, 2, and 3 spatial dimensions. The spectroscopic analysis methods discussed will be demonstrated to discern various common spectral and monoenergetic neutron sources.

Wetlands delineation by spectral signature analysis and legal implications

NASA Technical Reports Server (NTRS)

Anderon, R. R.; Carter, V.

1972-01-01

High altitude analysis of wetland resources and the use of such information in an operational mode to address specific problems of wetland preservation at a state level are discussed. Work efforts were directed toward: (1) developing techniques for using large scale color IR photography in state wetlands mapping program, (2) developing methods for obtaining wetlands ecology information from high altitude photography, (3) developing means by which spectral data can be more accurately analyzed visually, and (4) developing spectral data for automatic mapping of wetlands.

A fluctuation-induced plasma transport diagnostic based upon fast-Fourier transform spectral analysis

NASA Technical Reports Server (NTRS)

Powers, E. J.; Kim, Y. C.; Hong, J. Y.; Roth, J. R.; Krawczonek, W. M.

1978-01-01

A diagnostic, based on fast Fourier-transform spectral analysis techniques, that provides experimental insight into the relationship between the experimentally observable spectral characteristics of the fluctuations and the fluctuation-induced plasma transport is described. The model upon which the diagnostic technique is based and its experimental implementation is discussed. Some characteristic results obtained during the course of an experimental study of fluctuation-induced transport in the electric field dominated NASA Lewis bumpy torus plasma are presented.

Spectral Analysis within the Virtual Observatory: The GAVO Service TheoSSA

NASA Astrophysics Data System (ADS)

Ringat, E.

2012-03-01

In the last decade, numerous Virtual Observatory organizations were established. One of these is the German Astrophysical Virtual Observatory (GAVO) that e.g. provides access to spectral energy distributions via the service TheoSSA. In a pilot phase, these are based on the Tübingen NLTE Model-Atmosphere Package (TMAP) and suitable for hot, compact stars. We demonstrate the power of TheoSSA in an application to the sdOB primary of AA Doradus by comparison with a “classical” spectral analysis.

SearchLight: a freely available web-based quantitative spectral analysis tool (Conference Presentation)

NASA Astrophysics Data System (ADS)

Prabhat, Prashant; Peet, Michael; Erdogan, Turan

2016-03-01

In order to design a fluorescence experiment, typically the spectra of a fluorophore and of a filter set are overlaid on a single graph and the spectral overlap is evaluated intuitively. However, in a typical fluorescence imaging system the fluorophores and optical filters are not the only wavelength dependent variables - even the excitation light sources have been changing. For example, LED Light Engines may have a significantly different spectral response compared to the traditional metal-halide lamps. Therefore, for a more accurate assessment of fluorophore-to-filter-set compatibility, all sources of spectral variation should be taken into account simultaneously. Additionally, intuitive or qualitative evaluation of many spectra does not necessarily provide a realistic assessment of the system performance. "SearchLight" is a freely available web-based spectral plotting and analysis tool that can be used to address the need for accurate, quantitative spectral evaluation of fluorescence measurement systems. This tool is available at: http://searchlight.semrock.com/. Based on a detailed mathematical framework [1], SearchLight calculates signal, noise, and signal-to-noise ratio for multiple combinations of fluorophores, filter sets, light sources and detectors. SearchLight allows for qualitative and quantitative evaluation of the compatibility of filter sets with fluorophores, analysis of bleed-through, identification of optimized spectral edge locations for a set of filters under specific experimental conditions, and guidance regarding labeling protocols in multiplexing imaging assays. Entire SearchLight sessions can be shared with colleagues and collaborators and saved for future reference. [1] Anderson, N., Prabhat, P. and Erdogan, T., Spectral Modeling in Fluorescence Microscopy, http://www.semrock.com (2010).

Vertical shear-wave velocity profiles generated from spectral analysis of surface waves : field examples

DOT National Transportation Integrated Search

2003-04-01

Surface wave (Rayleigh wave) seismic data were acquired at six separate bridge sites in southeast Missouri. Each acquired surface wave data set was processed (spectral analysis of surface waves; SASW) and transformed into a site-specific vertical she...

Wavelet packets for multi- and hyper-spectral imagery

NASA Astrophysics Data System (ADS)

Benedetto, J. J.; Czaja, W.; Ehler, M.; Flake, C.; Hirn, M.

2010-01-01

State of the art dimension reduction and classification schemes in multi- and hyper-spectral imaging rely primarily on the information contained in the spectral component. To better capture the joint spatial and spectral data distribution we combine the Wavelet Packet Transform with the linear dimension reduction method of Principal Component Analysis. Each spectral band is decomposed by means of the Wavelet Packet Transform and we consider a joint entropy across all the spectral bands as a tool to exploit the spatial information. Dimension reduction is then applied to the Wavelet Packets coefficients. We present examples of this technique for hyper-spectral satellite imaging. We also investigate the role of various shrinkage techniques to model non-linearity in our approach.

Application of linear discriminant analysis and Attenuated Total Reflectance Fourier Transform Infrared microspectroscopy for diagnosis of colon cancer.

PubMed

Khanmohammadi, Mohammadreza; Bagheri Garmarudi, Amir; Samani, Simin; Ghasemi, Keyvan; Ashuri, Ahmad

2011-06-01

Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) microspectroscopy was applied for detection of colon cancer according to the spectral features of colon tissues. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. A total of 78 colon tissues were used in spectroscopy studies. Major spectral differences were observed in 1,740-900 cm(-1) spectral region. Several chemometric methods such as analysis of variance (ANOVA), cluster analysis (CA) and linear discriminate analysis (LDA) were applied for classification of IR spectra. Utilizing the chemometric techniques, clear and reproducible differences were observed between the spectra of normal and cancer cases, suggesting that infrared microspectroscopy in conjunction with spectral data processing would be useful for diagnostic classification. Using LDA technique, the spectra were classified into cancer and normal tissue classes with an accuracy of 95.8%. The sensitivity and specificity was 100 and 93.1%, respectively.

The Python Spectral Analysis Tool (PySAT) for Powerful, Flexible, and Easy Preprocessing and Machine Learning with Point Spectral Data

NASA Astrophysics Data System (ADS)

Anderson, R. B.; Finch, N.; Clegg, S. M.; Graff, T.; Morris, R. V.; Laura, J.

2018-04-01

The PySAT point spectra tool provides a flexible graphical interface, enabling scientists to apply a wide variety of preprocessing and machine learning methods to point spectral data, with an emphasis on multivariate regression.

The U. S. Geological Survey, Digital Spectral Library: Version 1 (0.2 to 3.0um)

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Gallagher, Andrea J.; King, Trude V.V.; Calvin, Wendy M.

1993-01-01

We have developed a digital reflectance spectral library, with management and spectral analysis software. The library includes 498 spectra of 444 samples (some samples include a series of grain sizes) measured from approximately 0.2 to 3.0 um . The spectral resolution (Full Width Half Maximum) of the reflectance data is <= 4 nm in the visible (0.2-0.8 um) and <= 10 nm in the NIR (0.8-2.35 um). All spectra were corrected to absolute reflectance using an NIST Halon standard. Library management software lets users search on parameters (e.g. chemical formulae, chemical analyses, purity of samples, mineral groups, etc.) as well as spectral features. Minerals from borate, carbonate, chloride, element, halide, hydroxide, nitrate, oxide, phosphate, sulfate, sulfide, sulfosalt, and the silicate (cyclosilicate, inosilicate, nesosilicate, phyllosilicate, sorosilicate, and tectosilicate) classes are represented. X-Ray and chemical analyses are tabulated for many of the entries, and all samples have been evaluated for spectral purity. The library also contains end and intermediate members for the olivine, garnet, scapolite, montmorillonite, muscovite, jarosite, and alunite solid-solution series. We have included representative spectra of H2O ice, kerogen, ammonium-bearing minerals, rare-earth oxides, desert varnish coatings, kaolinite crystallinity series, kaolinite-smectite series, zeolite series, and an extensive evaporite series. Because of the importance of vegetation to climate-change studies we have include 17 spectra of tree leaves, bushes, and grasses. The library and software are available as a series of U.S.G.S. Open File reports. PC user software is available to convert the binary data to ascii files (a separate U.S.G.S. open file report). Additionally, a binary data files are on line at the U.S.G.S. in Denver for anonymous ftp to users on the Internet. The library search software enables a user to search on documentation parameters as well as spectral features. The analysis system includes general spectral analysis routines, plotting packages, radiative transfer software for computing intimate mixtures, routines to derive optical constants from reflectance spectra, tools to analyze spectral features, and the capability to access imaging spectrometer data cubes for spectral analysis. Users may build customized libraries (at specific wavelengths and spectral resolution) for their own instruments using the library software. We are currently extending spectral coverage to 150 um. The libraries (original and convolved) will be made available in the future on a CD-ROM.

Spectral components in electromyograms from four regions of the human masseter, in natural dentate and edentulous subjects with removable prostheses and implants.

PubMed

Guzmán-Venegas, Rodrigo A; Palma, Felipe H; Biotti P, Jorge L; de la Rosa, Francisco J Berral

2018-06-01

To compare the frequency or spectral components between different regions of the superficial masseter in young natural dentate and total edentulous older adults rehabilitated with removable prostheses and fixed-implant support. A secondary objective was to compare these components between the three groups. 21 young natural dentate and 28 edentulous (14 with removable prostheses and 14 with fixed-implant support) were assessed. High-density surface electromyography (sEMG) was recorded in four portions of the superficial masseter during submaximal isometric bites. Spectral components were obtained through a spectral analysis of the sEMG signals. An analysis of mixed models was used to compare the spectral components. In all groups, the spectral components of the anterior portion were lower than in the posterior region (p < 0.05). Both edentulous groups showed lower spectral components and median frequency slope than the natural dentate group (p < 0.05). The removable prostheses group showed the greatest differences with natural dentate group. There were significant differences in the spectral components recorded in the different regions of the superficial masseter. The lower spectral components and fatigability of older adults rehabilitated with prostheses could be a cause of a greater loss of type II fibers, especially in the removable prostheses group. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spectral Analysis of Ultrasound Radiofrequency Backscatter for the Detection of Intercostal Blood Vessels.

PubMed

Klingensmith, Jon D; Haggard, Asher; Fedewa, Russell J; Qiang, Beidi; Cummings, Kenneth; DeGrande, Sean; Vince, D Geoffrey; Elsharkawy, Hesham

2018-04-19

Spectral analysis of ultrasound radiofrequency backscatter has the potential to identify intercostal blood vessels during ultrasound-guided placement of paravertebral nerve blocks and intercostal nerve blocks. Autoregressive models were used for spectral estimation, and bandwidth, autoregressive order and region-of-interest size were evaluated. Eight spectral parameters were calculated and used to create random forests. An autoregressive order of 10, bandwidth of 6 dB and region-of-interest size of 1.0 mm resulted in the minimum out-of-bag error. An additional random forest, using these chosen values, was created from 70% of the data and evaluated independently from the remaining 30% of data. The random forest achieved a predictive accuracy of 92% and Youden's index of 0.85. These results suggest that spectral analysis of ultrasound radiofrequency backscatter has the potential to identify intercostal blood vessels. (jokling@siue.edu) © 2018 World Federation for Ultrasound in Medicine and Biology. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Data analysis of multi-laser standoff spectral identification of chemical and biological compounds

NASA Astrophysics Data System (ADS)

Farahi, R.; Zaharov, V.; Tetard, L.; Thundat, T.; Passian, A.

2013-06-01

With the availability of tunable broadband coherent sources that emit mid-infrared radiation with well-defined beam characteristics, spectroscopies that were traditionally not practical for standoff detection1 or for development of miniaturized infrared detectors2, 3 have renewed interest. While obtaining compositional information for objects from a distance remains a major challenge in chemical and biological sensing, recently we demonstrated that capitalizing on mid-infrared excitation of target molecules by using quantum cascade lasers and invoking a pump probe scheme can provide spectral fingerprints of substances from a variable standoff distance.3 However, the standoff data is typically associated with random fluctuations that can corrupt the fine spectral features and useful data. To process the data from standoff experiments toward better recognition we consider and apply two types of denoising techniques, namely, spectral analysis and Karhunen-Loeve Transform (KLT). Using these techniques, infrared spectral data have been effectively improved. The result of the analysis illustrates that KLT can be adapted as a powerful data denoising tool for the presented pump-probe infrared standoff spectroscopy.

Extracting spectral contrast in Landsat Thematic Mapper image data using selective principal component analysis

USGS Publications Warehouse

Chavez, P.S.; Kwarteng, A.Y.

1989-01-01

A challenge encountered with Landsat Thematic Mapper (TM) data, which includes data from size reflective spectral bands, is displaying as much information as possible in a three-image set for color compositing or digital analysis. Principal component analysis (PCA) applied to the six TM bands simultaneously is often used to address this problem. However, two problems that can be encountered using the PCA method are that information of interest might be mathematically mapped to one of the unused components and that a color composite can be difficult to interpret. "Selective' PCA can be used to minimize both of these problems. The spectral contrast among several spectral regions was mapped for a northern Arizona site using Landsat TM data. Field investigations determined that most of the spectral contrast seen in this area was due to one of the following: the amount of iron and hematite in the soils and rocks, vegetation differences, standing and running water, or the presence of gypsum, which has a higher moisture retention capability than do the surrounding soils and rocks. -from Authors

Spectral Analysis of B Stars: An Application of Bayesian Statistics

NASA Astrophysics Data System (ADS)

Mugnes, J.-M.; Robert, C.

2012-12-01

To better understand the processes involved in stellar physics, it is necessary to obtain accurate stellar parameters (effective temperature, surface gravity, abundances…). Spectral analysis is a powerful tool for investigating stars, but it is also vital to reduce uncertainties at a decent computational cost. Here we present a spectral analysis method based on a combination of Bayesian statistics and grids of synthetic spectra obtained with TLUSTY. This method simultaneously constrains the stellar parameters by using all the lines accessible in observed spectra and thus greatly reduces uncertainties and improves the overall spectrum fitting. Preliminary results are shown using spectra from the Observatoire du Mont-Mégantic.

Low Cost Solar Array Project: Composition Measurements by Analytical Photon Catalysis

NASA Technical Reports Server (NTRS)

Sutton, D. G.; Galvan, L.; Melzer, J.; Heidner, R. F., III

1979-01-01

The applicability of the photon catalysis technique for effecting composition analysis of silicon samples was assessed. Third quarter activities were devoted to the study of impurities in silicon matrices. The evaporation process was shown to be congruent; thus, the spectral analysis of the vapor yields the composition of the bulk sample. Qualitative analysis of metal impurities in silicon was demonstrated e part per million level. Only one atomic spectral interference was noted; however, it is imperative to maintain a leak tight system due to chemical and spectral interferences caused by the presence of even minute amounts of oxygen in the active nitrogen afterglow.

MEM spectral analysis for predicting influenza epidemics in Japan.

PubMed

Sumi, Ayako; Kamo, Ken-ichi

2012-03-01

The prediction of influenza epidemics has long been the focus of attention in epidemiology and mathematical biology. In this study, we tested whether time series analysis was useful for predicting the incidence of influenza in Japan. The method of time series analysis we used consists of spectral analysis based on the maximum entropy method (MEM) in the frequency domain and the nonlinear least squares method in the time domain. Using this time series analysis, we analyzed the incidence data of influenza in Japan from January 1948 to December 1998; these data are unique in that they covered the periods of pandemics in Japan in 1957, 1968, and 1977. On the basis of the MEM spectral analysis, we identified the periodic modes explaining the underlying variations of the incidence data. The optimum least squares fitting (LSF) curve calculated with the periodic modes reproduced the underlying variation of the incidence data. An extension of the LSF curve could be used to predict the incidence of influenza quantitatively. Our study suggested that MEM spectral analysis would allow us to model temporal variations of influenza epidemics with multiple periodic modes much more effectively than by using the method of conventional time series analysis, which has been used previously to investigate the behavior of temporal variations in influenza data.

Spectral methods for time dependent problems

NASA Technical Reports Server (NTRS)

Tadmor, Eitan

1990-01-01

Spectral approximations are reviewed for time dependent problems. Some basic ingredients from the spectral Fourier and Chebyshev approximations theory are discussed. A brief survey was made of hyperbolic and parabolic time dependent problems which are dealt with by both the energy method and the related Fourier analysis. The ideas presented above are combined in the study of accuracy stability and convergence of the spectral Fourier approximation to time dependent problems.

Hyperspectral Imaging Sensors and the Marine Coastal Zone

NASA Technical Reports Server (NTRS)

Richardson, Laurie L.

2000-01-01

Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.

Augmented classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.; Melgaard, David K.

2004-02-03

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

Augmented Classical Least Squares Multivariate Spectral Analysis

DOEpatents

Haaland, David M.; Melgaard, David K.

2005-07-26

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

Augmented Classical Least Squares Multivariate Spectral Analysis

DOEpatents

Haaland, David M.; Melgaard, David K.

2005-01-11

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

Spectral Analysis of the Effects of Daylight Saving Time on Motor Vehicle Fatal Traffic Accidents

DOT National Transportation Integrated Search

1977-04-01

This report shows that Daylight Saving Time (DST) reduces the number of persons killed in motor vehicle fatal traffic accidents by about one percent. This estimate is based on a spectral (Fourier) analysis of these fatalities which utilizes a filteri...

A Modified Relative Spectral Mixture Analysis to Extract the Fractions of Major Land Cover Components

NASA Astrophysics Data System (ADS)

Jia, S.

2015-12-01

As an effective method of extracting land cover fractions based on spectral endmembers, spectral mixture analysis (SMA) has been applied using remotely sensed imagery in different spatial, temporal, and spectral resolutions. A number of studies focused on arid/semiarid ecosystem have used SMA to obtain the land cover fractions of GV, NPV/litter, and bare soil (BS) using MODIS reflectance products to understand ecosystem phenology, track vegetation dynamics, and evaluate the impact of major disturbances. However, several challenges remain in the application of SMA in studying ecosystem phenology, including obtaining high quality endmembers and increasing computational efficiency when considering to long time series that cover a broad spatial extent. Okin (2007) proposes a variation of SMA, named as relative spectra mixture analysis (RSMA) to address the latter challenge by calculating the relative change of fraction of GV, NPV/litter, and BS compared with a baseline date. This approach assumes that the baseline image contains the spectral information of the bare soil that can be used as an endmember for spectral mixture analysis though it is mixed with the spectral reflectance of other non-soil land cover types. Using the baseline image, one can obtain the change of fractions of GV, NPV/litter, BS, and snow compared with the baseline image. However, RSMA results depend on the selection of baseline date and the fractional components during this date. In this study, we modified the strategy of implementing RSMA by introducing a step of obtaining a soil map as the baseline image using multiple-endmember SMA (MESMA) before applying RSMA. The fractions of land cover components from this modified RSMA are also validated using the field observations from two study area in semiarid savanna and grassland of Queensland, Australia.

Short-Term EEG Spectral Pattern as a Single Event in EEG Phenomenology

PubMed Central

Fingelkurts, Al. A; Fingelkurts, An. A

2010-01-01

Spectral decomposition, to this day, still remains the main analytical paradigm for the analysis of EEG oscillations. However, conventional spectral analysis assesses the mean characteristics of the EEG power spectra averaged out over extended periods of time and/or broad frequency bands, thus resulting in a “static” picture which cannot reflect adequately the underlying neurodynamic. A relatively new promising area in the study of EEG is based on reducing the signal to elementary short-term spectra of various types in accordance with the number of types of EEG stationary segments instead of using averaged power spectrum for the whole EEG. It is suggested that the various perceptual and cognitive operations associated with a mental or behavioural condition constitute a single distinguishable neurophysiological state with a distinct and reliable spectral pattern. In this case, one type of short-term spectral pattern may be considered as a single event in EEG phenomenology. To support this assumption the following issues are considered in detail: (a) the relations between local EEG short-term spectral pattern of particular type and the actual state of the neurons in underlying network and a volume conduction; (b) relationship between morphology of EEG short-term spectral pattern and the state of the underlying neurodynamical system i.e. neuronal assembly; (c) relation of different spectral pattern components to a distinct physiological mechanism; (d) relation of different spectral pattern components to different functional significance; (e) developmental changes of spectral pattern components; (f) heredity of the variance in the individual spectral pattern and its components; (g) intra-individual stability of the sets of EEG short-term spectral patterns and their percent ratio; (h) discrete dynamics of EEG short-term spectral patterns. Functional relevance (consistency) of EEG short-term spectral patterns in accordance with the changes of brain functional state, cognitive task and with different neuropsychopathologies is demonstrated. PMID:21379390

Combined spectral-domain optical coherence tomography and hyperspectral imaging applied for tissue analysis: Preliminary results

NASA Astrophysics Data System (ADS)

Dontu, S.; Miclos, S.; Savastru, D.; Tautan, M.

2017-09-01

In recent years many optoelectronic techniques have been developed for improvement and the development of devices for tissue analysis. Spectral-Domain Optical Coherence Tomography (SD-OCT) is a new medical interferometric imaging modality that provides depth resolved tissue structure information with resolution in the μm range. However, SD-OCT has its own limitations and cannot offer the biochemical information of the tissue. These data can be obtained with hyperspectral imaging, a non-invasive, sensitive and real time technique. In the present study we have combined Spectral-Domain Optical Coherence Tomography (SD-OCT) with Hyperspectral imaging (HSI) for tissue analysis. The Spectral-Domain Optical Coherence Tomography (SD-OCT) and Hyperspectral imaging (HSI) are two methods that have demonstrated significant potential in this context. Preliminary results using different tissue have highlighted the capabilities of this technique of combinations.

Multispectral Photography

NASA Technical Reports Server (NTRS)

1982-01-01

Model II Multispectral Camera is an advanced aerial camera that provides optimum enhancement of a scene by recording spectral signatures of ground objects only in narrow, preselected bands of the electromagnetic spectrum. Its photos have applications in such areas as agriculture, forestry, water pollution investigations, soil analysis, geologic exploration, water depth studies and camouflage detection. The target scene is simultaneously photographed in four separate spectral bands. Using a multispectral viewer, such as their Model 75 Spectral Data creates a color image from the black and white positives taken by the camera. With this optical image analysis unit, all four bands are superimposed in accurate registration and illuminated with combinations of blue green, red, and white light. Best color combination for displaying the target object is selected and printed. Spectral Data Corporation produces several types of remote sensing equipment and also provides aerial survey, image processing and analysis and number of other remote sensing services.

New generation aircraft design problems relative to turbulence stability, aeroelastic loads and gust alleviation

NASA Technical Reports Server (NTRS)

Heimbaugh, Richard M.

1987-01-01

Past history, present status, and future of discrete gusts are schematically presented. It is shown that there are two approaches to the gust analysis: discrete and spectral density. The role of these two approaches to gust analysis are discussed. The idea of using power spectral density (PSD) in the analysis of gusts is especially detailed.

Spectral analysis of the structure of ultradispersed diamonds

NASA Astrophysics Data System (ADS)

Uglov, V. V.; Shimanski, V. I.; Rusalsky, D. P.; Samtsov, M. P.

2008-07-01

The structure of ultradispersed diamonds (UDD) is studied by spectral methods. The presence of diamond crystal phase in the UDD is found based on x-ray analysis and Raman spectra. The Raman spectra also show sp2-and sp3-hybridized carbon. Analysis of IR absorption spectra suggests that the composition of functional groups present in the particles changes during the treatment.

Spectral stability of unitary network models

NASA Astrophysics Data System (ADS)

Asch, Joachim; Bourget, Olivier; Joye, Alain

2015-08-01

We review various unitary network models used in quantum computing, spectral analysis or condensed matter physics and establish relationships between them. We show that symmetric one-dimensional quantum walks are universal, as are CMV matrices. We prove spectral stability and propagation properties for general asymptotically uniform models by means of unitary Mourre theory.

Spectral mixture modeling: Further analysis of rock and soil types at the Viking Lander sites

NASA Technical Reports Server (NTRS)

Adams, John B.; Smith, Milton O.

1987-01-01

A new image processing technique was applied to Viking Lander multispectral images. Spectral endmembers were defined that included soil, rock and shade. Mixtures of these endmembers were found to account for nearly all the spectral variance in a Viking Lander image.

Use of spectral analysis with iterative filter for voxelwise determination of regional rates of cerebral protein synthesis with L-[1-11C]leucine PET.

PubMed

Veronese, Mattia; Schmidt, Kathleen C; Smith, Carolyn Beebe; Bertoldo, Alessandra

2012-06-01

A spectral analysis approach was used to estimate kinetic parameters of the L-[1-(11)C]leucine positron emission tomography (PET) method and regional rates of cerebral protein synthesis (rCPS) on a voxel-by-voxel basis. Spectral analysis applies to both heterogeneous and homogeneous tissues; it does not require prior assumptions concerning number of tissue compartments. Parameters estimated with spectral analysis can be strongly affected by noise, but numerical filters improve estimation performance. Spectral analysis with iterative filter (SAIF) was originally developed to improve estimation of leucine kinetic parameters and rCPS in region-of-interest (ROI) data analyses. In the present study, we optimized SAIF for application at the voxel level. In measured L-[1-(11)C]leucine PET data, voxel-level SAIF parameter estimates averaged over all voxels within a ROI (mean voxel-SAIF) generally agreed well with corresponding estimates derived by applying the originally developed SAIF to ROI time-activity curves (ROI-SAIF). Region-of-interest-SAIF and mean voxel-SAIF estimates of rCPS were highly correlated. Simulations showed that mean voxel-SAIF rCPS estimates were less biased and less variable than ROI-SAIF estimates in the whole brain and cortex; biases were similar in white matter. We conclude that estimation of rCPS with SAIF is improved when the method is applied at voxel level than in ROI analysis.

Surface Composition of Trojan Asteroids from Thermal-Infrared Spectroscopy

NASA Astrophysics Data System (ADS)

Martin, A.; Emery, J. P.; Lindsay, S. S.

2017-12-01

Asteroid origins provide an effective means of constraining the events that dynamically shaped the solar system. Jupiter Trojan asteroids (hereafter Trojans) may help in determining the extent of radial mixing that occurred during giant planet migration. Previous studies aimed at characterizing surface composition show that Trojans have low albedo surfaces and fall into two distinct spectral groups the near infrared (NIR). Though, featureless in this spectral region, NIR spectra of Trojans either exhibit a red or less-red slope. Typically, red-sloped spectra are associated with organics, but it has been shown that Trojans are not host to much, if any, organic material. Instead, the red slope is likely due to anhydrous silicates. The thermal infrared (TIR) wavelength range has advantages for detecting silicates on low albedo asteroids such as Trojans. The 10 µm region exhibits strong features due to the Si-O fundamental molecular vibrations. We hypothesize that the two Trojan spectral groups have different compositions (silicate mineralogy). With TIR spectra from the Spitzer Space Telescope, we identify mineralogical features from the surface of 11 Trojan asteroids, five red and six less-red. Preliminary results from analysis of the 10 µm region indicate red-sloped Trojans have a higher spectral contrast compared to less-red-sloped Trojans. Fine-grain mixtures of crystalline pyroxene and olivine exhibit a 10 µm feature with sharp cutoffs between about 9 µm and 12 µm, which create a broad flat plateau. Amorphous phases, when present, smooth the sharp emission features, resulting in a dome-like shape. Further spectral analysis in the 10 µm, 18 µm, and 30 µm band region will be performed for a more robust analysis. If all Trojans come from the same region, it is expected that they share spectral and compositional characteristics. Therefore, if spectral analysis in the TIR reinforce the NIR spectral slope dichotomy, it is likely that Trojans were sourced from two different regions of the solar system. This result would provide new constraints for dynamical models that explain giant planet migration.

Photospheres of hot stars. IV - Spectral type O4

NASA Technical Reports Server (NTRS)

Bohannan, Bruce; Abbott, David C.; Voels, Stephen A.; Hummer, David G.

1990-01-01

The basic stellar parameters of a supergiant (Zeta Pup) and two main-sequence stars, 9 Sgr and HD 46223, at spectral class O4 are determined using line profile analysis. The stellar parameters are determined by comparing high signal-to-noise hydrogen and helium line profiles with those from stellar atmosphere models which include the effect of radiation scattered back onto the photosphere from an overlying stellar wind, an effect referred to as wind blanketing. At spectral class O4, the inclusion of wind-blanketing in the model atmosphere reduces the effective temperature by an average of 10 percent. This shift in effective temperature is also reflected by shifts in several other stellar parameters relative to previous O4 spectral-type calibrations. It is also shown through the analysis of the two O4 V stars that scatter in spectral type calibrations is introduced by assuming that the observed line profile reflects the photospheric stellar parameters.

Optimal wavelength band clustering for multispectral iris recognition.

PubMed

Gong, Yazhuo; Zhang, David; Shi, Pengfei; Yan, Jingqi

2012-07-01

This work explores the possibility of clustering spectral wavelengths based on the maximum dissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for iris multispectral fusion and to find these bands that will provide higher performance of iris multispectral recognition. A multispectral acquisition system was first designed for imaging the iris at narrow spectral bands in the range of 420 to 940 nm. Next, a set of 60 human iris images that correspond to the right and left eyes of 30 different subjects were acquired for an analysis. Finally, we determined that 3 clusters were enough to represent the 10 feature bands of spectral wavelengths using the agglomerative clustering based on two-dimensional principal component analysis. The experimental results suggest (1) the number, center, and composition of clusters of spectral wavelengths and (2) the higher performance of iris multispectral recognition based on a three wavelengths-bands fusion.

Analysis of the spectral vanishing viscosity method for periodic conservation laws

NASA Technical Reports Server (NTRS)

Maday, Yvon; Tadmor, Eitan

1988-01-01

The convergence of the spectral vanishing method for both the spectral and pseudospectral discretizations of the inviscid Burgers' equation is analyzed. It is proven that this kind of vanishing viscosity is responsible for a spectral decay of those Fourier coefficients located toward the end of the computed spectrum; consequently, the discretization error is shown to be spectrally small independent of whether the underlying solution is smooth or not. This in turn implies that the numerical solution remains uniformly bounded and convergence follows by compensated compactness arguments.

INSTRUMENTS AND METHODS OF INVESTIGATION: Spectral and spectral-frequency methods of investigating atmosphereless bodies of the Solar system

NASA Astrophysics Data System (ADS)

Busarev, Vladimir V.; Prokof'eva-Mikhailovskaya, Valentina V.; Bochkov, Valerii V.

2007-06-01

A method of reflectance spectrophotometry of atmosphereless bodies of the Solar system, its specificity, and the means of eliminating basic spectral noise are considered. As a development, joining the method of reflectance spectrophotometry with the frequency analysis of observational data series is proposed. The combined spectral-frequency method allows identification of formations with distinctive spectral features, and estimations of their sizes and distribution on the surface of atmospherelss celestial bodies. As applied to investigations of asteroids 21 Lutetia and 4 Vesta, the spectral frequency method has given us the possibility of obtaining fundamentally new information about minor planets.

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

NASA Technical Reports Server (NTRS)

Srivastava, Askok N.; Matthews, Bryan; Das, Santanu

2008-01-01

The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that can be taken to extract relevant features from these high-dimensional data streams. The first set of approaches relies on extracting features using a physics-based paradigm where the underlying physical mechanism that generates the spectra is used to infer the most important features in the data stream. We focus on a complementary methodology that uses a data-driven technique that is informed by the underlying physics but also has the ability to adapt to unmodeled system attributes and dynamics. We discuss the following four algorithms: Spectral Decomposition Algorithm (SDA), Non-Negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and Principal Components Analysis (PCA) and compare their performance on a spectral emulator which we use to generate artificial data with known statistical properties. This spectral emulator mimics the real-world phenomena arising from the plume of the space shuttle main engine and can be used to validate the results that arise from various spectral decomposition algorithms and is very useful for situations where real-world systems have very low probabilities of fault or failure. Our results indicate that methods like SDA and NMF provide a straightforward way of incorporating prior physical knowledge while NMF with a tuning mechanism can give superior performance on some tests. We demonstrate these algorithms to detect potential system-health issues on data from a spectral emulator with tunable health parameters.

Statistical properties of Fermi GBM GRBs' spectra

NASA Astrophysics Data System (ADS)

Rácz, István I.; Balázs, Lajos G.; Horvath, Istvan; Tóth, L. Viktor; Bagoly, Zsolt

2018-03-01

Statistical studies of gamma-ray burst (GRB) spectra may result in important information on the physics of GRBs. The Fermi GBM catalogue contains GRB parameters (peak energy, spectral indices, and intensity) estimated fitting the gamma-ray spectral energy distribution of the total emission (fluence, flnc), and during the time of the peak flux (pflx). Using contingency tables, we studied the relationship of the models best-fitting pflx and flnc time intervals. Our analysis revealed an ordering of the spectra into a power law - Comptonized - smoothly broken power law - Band series. This result was further supported by a correspondence analysis of the pflx and flnc spectra categorical variables. We performed a linear discriminant analysis (LDA) to find a relationship between categorical (spectral) and model independent physical data. LDA resulted in highly significant physical differences among the spectral types, that is more pronounced in the case of the pflx spectra, than for the flnc spectra. We interpreted this difference as caused by the temporal variation of the spectrum during the outburst. This spectral variability is confirmed by the differences in the low-energy spectral index and peak energy, between the pflx and flnc spectra. We found that the synchrotron radiation is significant in GBM spectra. The mean low-energy spectral index is close to the canonical value of α = -2/3 during the peak flux. However, α is ˜ -0.9 for the spectra of the fluences. We interpret this difference as showing that the effect of cooling is important only for the fluence spectra.

Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification

NASA Astrophysics Data System (ADS)

Sharif, I.; Khare, S.

2014-11-01

With the number of channels in the hundreds instead of in the tens Hyper spectral imagery possesses much richer spectral information than multispectral imagery. The increased dimensionality of such Hyper spectral data provides a challenge to the current technique for analyzing data. Conventional classification methods may not be useful without dimension reduction pre-processing. So dimension reduction has become a significant part of Hyper spectral image processing. This paper presents a comparative analysis of the efficacy of Haar and Daubechies wavelets for dimensionality reduction in achieving image classification. Spectral data reduction using Wavelet Decomposition could be useful because it preserves the distinction among spectral signatures. Daubechies wavelets optimally capture the polynomial trends while Haar wavelet is discontinuous and resembles a step function. The performance of these wavelets are compared in terms of classification accuracy and time complexity. This paper shows that wavelet reduction has more separate classes and yields better or comparable classification accuracy. In the context of the dimensionality reduction algorithm, it is found that the performance of classification of Daubechies wavelets is better as compared to Haar wavelet while Daubechies takes more time compare to Haar wavelet. The experimental results demonstrate the classification system consistently provides over 84% classification accuracy.

Research on marine and freshwater fish identification model based on hyper-spectral imaging technology

NASA Astrophysics Data System (ADS)

Fu, Yan; Guo, Pei-yuan; Xiang, Ling-zi; Bao, Man; Chen, Xing-hai

2013-08-01

With the gradually mature of hyper spectral image technology, the application of the meat nondestructive detection and recognition has become one of the current research focuses. This paper for the study of marine and freshwater fish by the pre-processing and feature extraction of the collected spectral curve data, combined with BP network structure and LVQ network structure, a predictive model of hyper spectral image data of marine and freshwater fish has been initially established and finally realized the qualitative analysis and identification of marine and freshwater fish quality. The results of this study show that hyper spectral imaging technology combined with the BP and LVQ Artificial Neural Network Model can be used for the identification of marine and freshwater fish detection. Hyper-spectral data acquisition can be carried out without any pretreatment of the samples, thus hyper-spectral imaging technique is the lossless, high- accuracy and rapid detection method for quality of fish. In this study, only 30 samples are used for the exploratory qualitative identification of research, although the ideal study results are achieved, we will further increase the sample capacity to take the analysis of quantitative identification and verify the feasibility of this theory.

Hyperspectral cytometry.

PubMed

Grégori, Gérald; Rajwa, Bartek; Patsekin, Valery; Jones, James; Furuki, Motohiro; Yamamoto, Masanobu; Paul Robinson, J

2014-01-01

Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each analyzed bioparticle onto linear detector arrays such as multianode photomultipliers or charge-coupled device sensors. The resultant data, consisting of a series of characterizing every analyzed cell, are not compensated by employing the traditional cytometry approach, but rather are spectrally unmixed utilizing algorithms such as constrained Poisson regression or non-negative matrix factorization. Although implementations of spectral cytometry were envisioned as early as the 1980s, only recently has the development of highly sensitive photomultiplier tube arrays led to design and construction of functional prototypes and subsequently to introduction of commercially available systems. This chapter summarizes the historical efforts and work in the field of spectral cytometry performed at Purdue University Cytometry Laboratories and describes the technology developed by Sony Corporation that resulted in release of the first commercial spectral cytometry system-the Sony SP6800. A brief introduction to spectral data analysis is also provided, with emphasis on the differences between traditional polychromatic and spectral cytometry approaches.

Hyperspectral image analysis for the determination of alteration minerals in geothermal fields: Çürüksu (Denizli) Graben, Turkey

NASA Astrophysics Data System (ADS)

Uygur, Merve; Karaman, Muhittin; Kumral, Mustafa

2016-04-01

Çürüksu (Denizli) Graben hosts various geothermal fields such as Kızıldere, Yenice, Gerali, Karahayıt, and Tekkehamam. Neotectonic activities, which are caused by extensional tectonism, and deep circulation in sub-volcanic intrusions are heat sources of hydrothermal solutions. The temperature of hydrothermal solutions is between 53 and 260 degree Celsius. Phyllic, argillic, silicic, and carbonatization alterations and various hydrothermal minerals have been identified in various research studies of these areas. Surfaced hydrothermal alteration minerals are one set of potential indicators of geothermal resources. Developing the exploration tools to define the surface indicators of geothermal fields can assist in the recognition of geothermal resources. Thermal and hyperspectral imaging and analysis can be used for defining the surface indicators of geothermal fields. This study tests the hypothesis that hyperspectral image analysis based on EO-1 Hyperion images can be used for the delineation and definition of surfaced hydrothermal alteration in geothermal fields. Hyperspectral image analyses were applied to images covering the geothermal fields whose alteration characteristic are known. To reduce data dimensionality and identify spectral endmembers, Kruse's multi-step process was applied to atmospherically and geometrically-corrected hyperspectral images. Minimum Noise Fraction was used to reduce the spectral dimensions and isolate noise in the images. Extreme pixels were identified from high order MNF bands using the Pixel Purity Index. n-Dimensional Visualization was utilized for unique pixel identification. Spectral similarities between pixel spectral signatures and known endmember spectrum (USGS Spectral Library) were compared with Spectral Angle Mapper Classification. EO-1 Hyperion hyperspectral images and hyperspectral analysis are sensitive to hydrothermal alteration minerals, as their diagnostic spectral signatures span the visible and shortwave infrared seen in geothermal fields. Hyperspectral analysis results indicated that kaolinite, smectite, illite, montmorillonite, and sepiolite minerals were distributed in a wide area, which covered the hot spring outlet. Rectorite, lizardite, richterite, dumortierite, nontronite, erionite, and clinoptilolite were observed occasionally.

Models and methods to characterize site amplification from a pair of records

USGS Publications Warehouse

Safak, E.

1997-01-01

The paper presents a tutorial review of the models and methods that are used to characterize site amplification from the pairs of rock- and soil-site records, and introduces some new techniques with better theoretical foundations. The models and methods discussed include spectral and cross-spectral ratios, spectral ratios for downhole records, response spectral ratios, constant amplification factors, parametric models, physical models, and time-varying filters. An extensive analytical and numerical error analysis of spectral and cross-spectral ratios shows that probabilistically cross-spectral ratios give more reliable estimates of site amplification. Spectral ratios should not be used to determine site amplification from downhole-surface recording pairs because of the feedback in the downhole sensor. Response spectral ratios are appropriate for low frequencies, but overestimate the amplification at high frequencies. The best method to be used depends on how much precision is required in the estimates.

Library Optimization in EDXRF Spectral Deconvolution for Multi-element Analysis of Ambient Aerosols

EPA Science Inventory

In multi-element analysis of atmospheric aerosols, attempts are made to fit overlapping elemental spectral lines for many elements that may be undetectable in samples due to low concentrations. Fitting with many library reference spectra has the unwanted effect of raising the an...

Nearest clusters based partial least squares discriminant analysis for the classification of spectral data.

PubMed

Song, Weiran; Wang, Hui; Maguire, Paul; Nibouche, Omar

2018-06-07

Partial Least Squares Discriminant Analysis (PLS-DA) is one of the most effective multivariate analysis methods for spectral data analysis, which extracts latent variables and uses them to predict responses. In particular, it is an effective method for handling high-dimensional and collinear spectral data. However, PLS-DA does not explicitly address data multimodality, i.e., within-class multimodal distribution of data. In this paper, we present a novel method termed nearest clusters based PLS-DA (NCPLS-DA) for addressing the multimodality and nonlinearity issues explicitly and improving the performance of PLS-DA on spectral data classification. The new method applies hierarchical clustering to divide samples into clusters and calculates the corresponding centre of every cluster. For a given query point, only clusters whose centres are nearest to such a query point are used for PLS-DA. Such a method can provide a simple and effective tool for separating multimodal and nonlinear classes into clusters which are locally linear and unimodal. Experimental results on 17 datasets, including 12 UCI and 5 spectral datasets, show that NCPLS-DA can outperform 4 baseline methods, namely, PLS-DA, kernel PLS-DA, local PLS-DA and k-NN, achieving the highest classification accuracy most of the time. Copyright © 2018 Elsevier B.V. All rights reserved.

Reliable Quantitative Mineral Abundances of the Martian Surface using THEMIS

NASA Astrophysics Data System (ADS)

Smith, R. J.; Huang, J.; Ryan, A. J.; Christensen, P. R.

2013-12-01

The following presents a proof of concept that given quality data, Thermal Emission Imaging System (THEMIS) data can be used to derive reliable quantitative mineral abundances of the Martian surface using a limited mineral library. The THEMIS instrument aboard the Mars Odyssey spacecraft is a multispectral thermal infrared imager with a spatial resolution of 100 m/pixel. The relatively high spatial resolution along with global coverage makes THEMIS datasets powerful tools for comprehensive fine scale petrologic analyses. However, the spectral resolution of THEMIS is limited to 8 surface sensitive bands between 6.8 and 14.0 μm with an average bandwidth of ~ 1 μm, which complicates atmosphere-surface separation and spectral analysis. This study utilizes the atmospheric correction methods of both Bandfield et al. [2004] and Ryan et al. [2013] joined with the iterative linear deconvolution technique pioneered by Huang et al. [in review] in order to derive fine-scale quantitative mineral abundances of the Martian surface. In general, it can be assumed that surface emissivity combines in a linear fashion in the thermal infrared (TIR) wavelengths such that the emitted energy is proportional to the areal percentage of the minerals present. TIR spectra are unmixed using a set of linear equations involving an endmember library of lab measured mineral spectra. The number of endmembers allowed in a spectral library are restricted to a quantity of n-1 (where n = the number of spectral bands of an instrument), preserving one band for blackbody. Spectral analysis of THEMIS data is thus allowed only seven endmembers. This study attempts to prove that this limitation does not prohibit the derivation of meaningful spectral analyses from THEMIS data. Our study selects THEMIS stamps from a region of Mars that is well characterized in the TIR by the higher spectral resolution, lower spatial resolution Thermal Emission Spectrometer (TES) instrument (143 bands at 10 cm-1 sampling and 3x5 km pixel). Multiple atmospheric corrections are performed for one image using the methods of Bandfield et al. [2004] and Ryan et al. [2013]. 7x7 pixel areas were selected, averaged, and compared using each atmospherically corrected image to ensure consistency. Corrections that provided reliable data were then used for spectral analyses. Linear deconvolution is performed using an iterative spectral analysis method [Huang et al. in review] that takes an endmember spectral library, and creates mineral combinations based on prescribed mineral group selections. The script then performs a spectral mixture analysis on each surface spectrum using all possible mineral combinations, and reports the best modeled fit to the measured spectrum. Here we present initial results from Syrtis Planum where multiple atmospherically corrected THEMIS images were deconvolved to produce similar spectral analysis results, within the detection limit of the instrument. THEMIS mineral abundances are comparable to TES-derived abundances. References: Bandfield, JL et al. [2004], JGR 109, E10008 Huang, J et al., JGR, in review Ryan, AJ et al. [2013], AGU Fall Meeting

Distinguishability of stacks in ZnTe/ZnSe quantum dots via spectral analysis of Aharonov-Bohm oscillations

NASA Astrophysics Data System (ADS)

Roy, Bidisha; Ji, Haojie; Dhomkar, Siddharth; Cadieu, Fred J.; Peng, Le; Moug, Richard; Tamargo, Maria C.; Kuskovsky, Igor L.

2013-02-01

A spectral analysis of the Aharonov-Bohm (AB) oscillations in photoluminescence intensity was performed for stacked type-II ZnTe/ZnSe quantum dots (QDs) fabricated within multilayered Zn-Se-Te system with sub-monolayer insertions of Te. Robust AB oscillations allowed for fine probing of distinguishable QDs stacks within the ensemble of QDs. The AB transition magnetic field, B AB , changed from the lower energy side to the higher energy side of the PL spectra revealing the presence of different sets of QDs stacks. The change occurs within the spectral range, where the contributing green and blue bands of the spectra overlapped. "Bundling" in lifetime measurements is seen at transition spectral regions confirming the results.

Classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.

2002-01-01

An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLS-type methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.

New parameter of the right gastroepiploic arterial graft using the power spectral analysis device named MemCalc soft.

PubMed

Uehara, Mayuko; Takagi, Nobuyuki; Muraki, Satoshi; Yanase, Yosuke; Tabuchi, Masaki; Tachibana, Kazutoshi; Miyaki, Yasuko; Ito, Toshiro; Higami, Tetsuya

2015-12-01

Transit-time flow measurement (TTFM) parameters such as mean graft flow (MGF, ml/min), pulsatility index (PI) and diastolic filling (DF, %) have been extensively researched for internal mammary arterial or saphenous vein grafts. In our experience of using the right gastroepiploic arterial (GEA) graft for right coronary artery (RCA) grafting, we observed unique GEA graft flow waveforms. We analysed the GEA graft flow waveforms for their effectiveness in determining GEA graft patency by power spectral analysis. Forty-five patients underwent off-pump coronary artery bypass using the GEA graft for RCA grafting individually. The means of intraoperative MGF, PI and DF were compared between patent and non-patent grafts, postoperatively. Furthermore, the GEA flow data were output and analysed using power spectral analysis. Forty grafts were 'patent' and five were 'non-patent'. There were no significant differences in the mean TTFM parameters between the patent and non-patent grafts (MGF: 22 vs 8 ml/min, respectively, P = 0.068; PI: 3.5 vs 6.5, respectively, P = 0.155; DF: 63 vs 53%, respectively, P = 0.237). Results of the power spectral analysis presented clear differences; the power spectral density (PSD) of patent grafts presented high peaks at frequency levels of 1, 2 and 3 Hz, and the non-patent graft PSD presented high peaks that were not limited to these frequencies. The PSD had a sensitivity and specificity of 80 and 87.5%, respectively. Power spectral analysis of the GEA graft flow is useful to distinguish between non-patent and patent grafts intraoperatively. This should be used as a fourth parameter along with MGF, PI and DF. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

[Experimental Methods and Result Analysis of a Variety of Spectral Reflectance Properties of the Thin Oil Film].

PubMed

Ye, Zhou; Liu, Li; Wei, Chuan-xin; Gu, Qun; An, Ping-ao; Zhao, Yue-jiao; Yin, Da-yi

2015-06-01

In order to analysis the oil spill situation based on the obtained data in airborne aerial work, it's needed to get the spectral reflectance characteristics of the oil film of different oils and thickness as support and to select the appropriate operating band. An experiment is set up to measure the reflectance spectroscopy from ultraviolet to near-infrared for the film of five target samples, which means petrol, diesel, lubricating oil, kerosene and fossil, using spectral measurement device. The result is compared with the reflectance spectra of water in the same experimental environment, which shows that the spectral reflection characteristics of the oil film are related to the thickness and the type of the oil film. In case of the same thickness, the spectral reflectance curve of different types of film is far different, and for the same type of film, the spectral reflectance curve changes accordingly with the change of film thickness, therefore in terms of the single film, different film thickness can be distinguished by reflectance curves. It also shows that in terms of the same film thickness, the reflectance of diesel, kerosene, lubricants reaches peak around 380 nm wavelength, obviously different from the reflectance of water, and that the reflectance of crude oil is far less than that of water in more than 340 nm wavelength, and the obtained reflection spectrum can be used to distinguish between different types of oil film to some extent. The experiment covers main types of spilled oil, with data comprehensively covering commonly used detect spectral bands, and quantitative description of the spectral reflectance properties of film. It provides comprehensive theoretical and data support for the selection of airborne oil spill detection working band and the detection and analysis of water-surface oil spill.

Integration of multispectral satellite and hyperspectral field data for aquatic macrophyte studies

NASA Astrophysics Data System (ADS)

John, C. M.; Kavya, N.

2014-11-01

Aquatic macrophytes (AM) can serve as useful indicators of water pollution along the littoral zones. The spectral signatures of various AM were investigated to determine whether species could be discriminated by remote sensing. In this study the spectral readings of different AM communities identified were done using the ASD Fieldspec® Hand Held spectro-radiometer in the wavelength range of 325-1075 nm. The collected specific reflectance spectra were applied to space borne multi-spectral remote sensing data from Worldview-2, acquired on 26th March 2011. The dimensionality reduction of the spectro-radiometric data was done using the technique principal components analysis (PCA). Out of the different PCA axes generated, 93.472 % variance of the spectra was explained by the first axis. The spectral derivative analysis was done to identify the wavelength where the greatest difference in reflectance is shown. The identified wavelengths are 510, 690, 720, 756, 806, 885, 907 and 923 nm. The output of PCA and derivative analysis were applied to Worldview-2 satellite data for spectral subsetting. The unsupervised classification was used to effectively classify the AM species using the different spectral subsets. The accuracy assessment of the results of the unsupervised classification and their comparison were done. The overall accuracy of the result of unsupervised classification using the band combinations Red-Edge, Green, Coastal blue & Red-edge, Yellow, Blue is 100%. The band combinations NIR-1, Green, Coastal blue & NIR-1, Yellow, Blue yielded an accuracy of 82.35 %. The existing vegetation indices and new hyper-spectral indices for the different type of AM communities were computed. Overall, results of this study suggest that high spectral and spatial resolution images provide useful information for natural resource managers especially with regard to the location identification and distribution mapping of macrophyte species and their communities.

Solid state linear dichroic infrared spectral analysis of benzimidazoles and their N 1-protonated salts

NASA Astrophysics Data System (ADS)

Ivanova, B. B.

2005-11-01

A stereo structural characterization of 2,5,6-thrimethylbenzimidazole (MBIZ) and 2-amino-benzimidaziole (2-NH 2-BI) and their N 1 protonation salts was carried out using a polarized solid state linear dichroic infrared spectral (IR-LD) analysis in nematic liquid crystal suspension. All experimental predicted structures were compared with the theoretical ones, obtained by ab initio calculations. The Cs to C2v* symmetry transformation as a result of protonation processes, with a view of its reflection on the infrared spectral characteristics was described.

Spectral Discrete Probability Density Function of Measured Wind Turbine Noise in the Far Field

PubMed Central

Ashtiani, Payam; Denison, Adelaide

2015-01-01

Of interest is the spectral character of wind turbine noise at typical residential set-back distances. In this paper, a spectral statistical analysis has been applied to immission measurements conducted at three locations. This method provides discrete probability density functions for the Turbine ONLY component of the measured noise. This analysis is completed for one-third octave sound levels, at integer wind speeds, and is compared to existing metrics for measuring acoustic comfort as well as previous discussions on low-frequency noise sources. PMID:25905097

A spatio-spectral polarization analysis of 1 µm-pumped bulk supercontinuum in a cubic crystal (YAG)

NASA Astrophysics Data System (ADS)

Choudhuri, Aradhana; Chatterjee, Gourab; Zheng, Jiaan; Hartl, Ingmar; Ruehl, Axel; Dwayne Miller, R. J.

2018-06-01

We present the first systematic study of the spatio-spectral polarization properties of a supercontinuum generated in a cubic crystal, yttrium-aluminum garnet (YAG), including a full spectral analysis of the white light core and surrounding ring structure. We observe no depolarization of the supercontinuum, and no spatial dependence of polarization ratios for any wavelength. We discuss the discrepancy of YAG's polarization behavior in the context of well-established results in literature reporting self-induced depolarization in other cubic crystals.

Wavelets, non-linearity and turbulence in fusion plasmas

NASA Astrophysics Data System (ADS)

van Milligen, B. Ph.

Introduction Linear spectral analysis tools Wavelet analysis Wavelet spectra and coherence Joint wavelet phase-frequency spectra Non-linear spectral analysis tools Wavelet bispectra and bicoherence Interpretation of the bicoherence Analysis of computer-generated data Coupled van der Pol oscillators A large eddy simulation model for two-fluid plasma turbulence A long wavelength plasma drift wave model Analysis of plasma edge turbulence from Langmuir probe data Radial coherence observed on the TJ-IU torsatron Bicoherence profile at the L/H transition on CCT Conclusions

Spectral element multigrid. Part 2: Theoretical justification

NASA Technical Reports Server (NTRS)

Maday, Yvon; Munoz, Rafael

1988-01-01

A multigrid algorithm is analyzed which is used for solving iteratively the algebraic system resulting from tha approximation of a second order problem by spectral or spectral element methods. The analysis, performed here in the one dimensional case, justifies the good smoothing properties of the Jacobi preconditioner that was presented in Part 1 of this paper.

A 1064 nm dispersive Raman spectral imaging system for food safety and quality evaluation

USDA-ARS?s Scientific Manuscript database

Raman spectral imaging is an effective method to analyze and evaluate chemical composition and structure of a sample, and has many applications for food safety and quality research. This study developed a 1064 nm Raman spectral imaging system for surface and subsurface analysis of food samples. A 10...

Analysis of airborne MAIS imaging spectrometric data for mineral exploration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang Jinnian; Zheng Lanfen; Tong Qingxi

1996-11-01

The high spectral resolution imaging spectrometric system made quantitative analysis and mapping of surface composition possible. The key issue will be the quantitative approach for analysis of surface parameters for imaging spectrometer data. This paper describes the methods and the stages of quantitative analysis. (1) Extracting surface reflectance from imaging spectrometer image. Lab. and inflight field measurements are conducted for calibration of imaging spectrometer data, and the atmospheric correction has also been used to obtain ground reflectance by using empirical line method and radiation transfer modeling. (2) Determining quantitative relationship between absorption band parameters from the imaging spectrometer data andmore » chemical composition of minerals. (3) Spectral comparison between the spectra of spectral library and the spectra derived from the imagery. The wavelet analysis-based spectrum-matching techniques for quantitative analysis of imaging spectrometer data has beer, developed. Airborne MAIS imaging spectrometer data were used for analysis and the analysis results have been applied to the mineral and petroleum exploration in Tarim Basin area china. 8 refs., 8 figs.« less

Breast tissue decomposition with spectral distortion correction: A postmortem study

PubMed Central

Ding, Huanjun; Zhao, Bo; Baturin, Pavlo; Behroozi, Farnaz; Molloi, Sabee

2014-01-01

Purpose: To investigate the feasibility of an accurate measurement of water, lipid, and protein composition of breast tissue using a photon-counting spectral computed tomography (CT) with spectral distortion corrections. Methods: Thirty-eight postmortem breasts were imaged with a cadmium-zinc-telluride-based photon-counting spectral CT system at 100 kV. The energy-resolving capability of the photon-counting detector was used to separate photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose for each breast ranged from 1.8 to 2.2 mGy. Two spectral distortion correction techniques were implemented, respectively, on the raw images to correct the nonlinear detector response due to pulse pileup and charge-sharing artifacts. Dual energy decomposition was then used to characterize each breast in terms of water, lipid, and protein content. In the meantime, the breasts were chemically decomposed into their respective water, lipid, and protein components to provide a gold standard for comparison with dual energy decomposition results. Results: The accuracy of the tissue compositional measurement with spectral CT was determined by comparing to the reference standard from chemical analysis. The averaged root-mean-square error in percentage composition was reduced from 15.5% to 2.8% after spectral distortion corrections. Conclusions: The results indicate that spectral CT can be used to quantify the water, lipid, and protein content in breast tissue. The accuracy of the compositional analysis depends on the applied spectral distortion correction technique. PMID:25281953

Research on hyperspectral dynamic scene and image sequence simulation

NASA Astrophysics Data System (ADS)

Sun, Dandan; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei

2016-10-01

This paper presents a simulation method of hyper-spectral dynamic scene and image sequence for hyper-spectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyper-spectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyper-spectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyper-spectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyper-spectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyper-spectral images are consistent with the theoretical analysis results.

Prediction Analysis for Measles Epidemics

NASA Astrophysics Data System (ADS)

Sumi, Ayako; Ohtomo, Norio; Tanaka, Yukio; Sawamura, Sadashi; Olsen, Lars Folke; Kobayashi, Nobumichi

2003-12-01

A newly devised procedure of prediction analysis, which is a linearized version of the nonlinear least squares method combined with the maximum entropy spectral analysis method, was proposed. This method was applied to time series data of measles case notification in several communities in the UK, USA and Denmark. The dominant spectral lines observed in each power spectral density (PSD) can be safely assigned as fundamental periods. The optimum least squares fitting (LSF) curve calculated using these fundamental periods can essentially reproduce the underlying variation of the measles data. An extension of the LSF curve can be used to predict measles case notification quantitatively. Some discussions including a predictability of chaotic time series are presented.

Spectral analysis of sinus arrhythmia - A measure of mental effort

NASA Technical Reports Server (NTRS)

Vicente, Kim J.; Craig Thornton, D.; Moray, Neville

1987-01-01

The validity of the spectral analysis of sinus arrhythmia as a measure of mental effort was investigated using a computer simulation of a hovercraft piloted along a river as the experimental task. Strong correlation was observed between the subjective effort-ratings and the heart-rate variability (HRV) power spectrum between 0.06 and 0.14 Hz. Significant correlations were observed not only between subjects but, more importantly, within subjects as well, indicating that the spectral analysis of HRV is an accurate measure of the amount of effort being invested by a subject. Results also indicate that the intensity of effort invested by subjects cannot be inferred from the objective ratings of task difficulty or from performance.

Sensitive sub-Doppler nonlinear spectroscopy for hyperfine-structure analysis using simple atomizers

NASA Astrophysics Data System (ADS)

Mickadeit, Fritz K.; Kemp, Helen; Schafer, Julia; Tong, William M.

1998-05-01

Laser wave-mixing spectroscopy is presented as a sub-Doppler method that offers not only high spectral resolution, but also excellent detection sensitivity. It offers spectral resolution suitable for hyperfine structure analysis and isotope ratio measurements. In a non-planar backward- scattering four-wave mixing optical configuration, two of the three input beams counter propagate and the Doppler broadening is minimized, and hence, spectral resolution is enhanced. Since the signal is a coherent beam, optical collection is efficient and signal detection is convenient. This simple multi-photon nonlinear laser method offers un usually sensitive detection limits that are suitable for trace-concentration isotope analysis using a few different types of simple analytical atomizers. Reliable measurement of hyperfine structures allows effective determination of isotope ratios for chemical analysis.

Transitions in effective scaling behavior of accelerometric time series across sleep and wake

NASA Astrophysics Data System (ADS)

Wohlfahrt, Patrick; Kantelhardt, Jan W.; Zinkhan, Melanie; Schumann, Aicko Y.; Penzel, Thomas; Fietze, Ingo; Pillmann, Frank; Stang, Andreas

2013-09-01

We study the effective scaling behavior of high-resolution accelerometric time series recorded at the wrists and hips of 100 subjects during sleep and wake. Using spectral analysis and detrended fluctuation analysis we find long-term correlated fluctuations with a spectral exponent \\beta \\approx 1.0 (1/f noise). On short time scales, β is larger during wake (\\approx 1.4 ) and smaller during sleep (\\approx 0.6 ). In addition, characteristic peaks at 0.2-0.3 Hz (due to respiration) and 4-10 Hz (probably due to physiological tremor) are observed in periods of weak activity. Because of these peaks, spectral analysis is superior in characterizing effective scaling during sleep, while detrending analysis performs well during wake. Our findings can be exploited to detect sleep-wake transitions.

Rapid Elemental Analysis and Provenance Study of Blumea balsamifera DC Using Laser-Induced Breakdown Spectroscopy

PubMed Central

Liu, Xiaona; Zhang, Qiao; Wu, Zhisheng; Shi, Xinyuan; Zhao, Na; Qiao, Yanjiang

2015-01-01

Laser-induced breakdown spectroscopy (LIBS) was applied to perform a rapid elemental analysis and provenance study of Blumea balsamifera DC. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were implemented to exploit the multivariate nature of the LIBS data. Scores and loadings of computed principal components visually illustrated the differing spectral data. The PLS-DA algorithm showed good classification performance. The PLS-DA model using complete spectra as input variables had similar discrimination performance to using selected spectral lines as input variables. The down-selection of spectral lines was specifically focused on the major elements of B. balsamifera samples. Results indicated that LIBS could be used to rapidly analyze elements and to perform provenance study of B. balsamifera. PMID:25558999

Semiclassical analysis of spectral singularities and their applications in optics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mostafazadeh, Ali

2011-08-15

Motivated by possible applications of spectral singularities in optics, we develop a semiclassical method of computing spectral singularities. We use this method to examine the spectral singularities of a planar slab gain medium whose gain coefficient varies due to the exponential decay of the intensity of the pumping beam inside the medium. For both singly and doublypumped samples, we obtain universal upper bounds on the decay constant beyond which no lasing occurs. Furthermore, we show that the dependence of the wavelength of the spectral singularities on the value of the decay constant is extremely mild. This is an indication ofmore » the stability of optical spectral singularities.« less

Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis

NASA Astrophysics Data System (ADS)

Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.

2013-06-01

Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.

(abstract) Cross with Your Spectra? Cross-Correlate Instead!

NASA Technical Reports Server (NTRS)

Beer, Reinhard

1994-01-01

The use of cross-correlation for certain types of spectral analysis is discussed. Under certain circumstances, the use of cross-correlation between a real spectrum and either a model or another spectrum can provide a very powerful tool for spectral analysis. The method (and its limitations) will be described with concrete examples using ATMOS data.

Mass spectral analysis of C3 and C4 aliphatic amino acid derivatives.

NASA Technical Reports Server (NTRS)

Lawless, J. G.; Chadha, M. S.

1971-01-01

Diagnostic criteria are obtained for the distinction of alpha, beta, gamma, and N-methyl isomers of the C3 and C4 aliphatic amino acids, using mass spectral analysis of the derivatives of these acids. The use of deuterium labeling has helped in the understanding of certain fragmentation pathways.

Discriminant Analysis of Time Series in the Presence of Within-Group Spectral Variability.

PubMed

Krafty, Robert T

2016-07-01

Many studies record replicated time series epochs from different groups with the goal of using frequency domain properties to discriminate between the groups. In many applications, there exists variation in cyclical patterns from time series in the same group. Although a number of frequency domain methods for the discriminant analysis of time series have been explored, there is a dearth of models and methods that account for within-group spectral variability. This article proposes a model for groups of time series in which transfer functions are modeled as stochastic variables that can account for both between-group and within-group differences in spectra that are identified from individual replicates. An ensuing discriminant analysis of stochastic cepstra under this model is developed to obtain parsimonious measures of relative power that optimally separate groups in the presence of within-group spectral variability. The approach possess favorable properties in classifying new observations and can be consistently estimated through a simple discriminant analysis of a finite number of estimated cepstral coefficients. Benefits in accounting for within-group spectral variability are empirically illustrated in a simulation study and through an analysis of gait variability.

Computerized EEG analysis for studying the effect of drugs on the central nervous system.

PubMed

Rosadini, G; Cavazza, B; Rodriguez, G; Sannita, W G; Siccardi, A

1977-11-01

Samples of our experience in quantitative pharmaco-EEG are reviewed to discuss and define its applicability and limits. Simple processing systems, such as the computation of Hjorth's descriptors, are useful for on-line monitoring of drug-induced EEG modifications which are evident also at the visual visual analysis. Power spectral analysis is suitable to identify and quantify EEG effects not evident at the visual inspection. It demonstrated how the EEG effects of compounds in a long-acting formulation vary according to the sampling time and the explored cerebral area. EEG modifications not detected by power spectral analysis can be defined by comparing statistically (F test) the spectral values of the EEG from a single lead at the different samples (longitudinal comparison), or the spectral values from different leads at any sample (intrahemispheric comparison). The presently available procedures of quantitative pharmaco-EEG are effective when applied to the study of mutltilead EEG recordings in a statistically significant sample of population. They do not seem reliable in the monitoring of directing of neuropyschiatric therapies in single patients, due to individual variability of drug effects.

A study of the application of power-spectral methods of generalized harmonic analysis to gust loads on airplanes

NASA Technical Reports Server (NTRS)

Press, Harry; Mazelsky, Bernard

1954-01-01

The applicability of some results from the theory of generalized harmonic analysis (or power-spectral analysis) to the analysis of gust loads on airplanes in continuous rough air is examined. The general relations for linear systems between power spectrums of a random input disturbance and an output response are used to relate the spectrum of airplane load in rough air to the spectrum of atmospheric gust velocity. The power spectrum of loads is shown to provide a measure of the load intensity in terms of the standard deviation (root mean square) of the load distribution for an airplane in flight through continuous rough air. For the case of a load output having a normal distribution, which appears from experimental evidence to apply to homogeneous rough air, the standard deviation is shown to describe the probability distribution of loads or the proportion of total time that the load has given values. Thus, for airplane in flight through homogeneous rough air, the probability distribution of loads may be determined from a power-spectral analysis. In order to illustrate the application of power-spectral analysis to gust-load analysis and to obtain an insight into the relations between loads and airplane gust-response characteristics, two selected series of calculations are presented. The results indicate that both methods of analysis yield results that are consistent to a first approximation.

Group Independent Component Analysis (gICA) and Current Source Density (CSD) in the study of EEG in ADHD adults.

PubMed

Ponomarev, Valery A; Mueller, Andreas; Candrian, Gian; Grin-Yatsenko, Vera A; Kropotov, Juri D

2014-01-01

To investigate the performance of the spectral analysis of resting EEG, Current Source Density (CSD) and group independent components (gIC) in diagnosing ADHD adults. Power spectra of resting EEG, CSD and gIC (19 channels, linked ears reference, eyes open/closed) from 96 ADHD and 376 healthy adults were compared between eyes open and eyes closed conditions, and between groups of subjects. Pattern of differences in gIC and CSD spectral power between conditions was approximately similar, whereas it was more widely spatially distributed for EEG. Size effect (Cohen's d) of differences in gIC and CSD spectral power between groups of subjects was considerably greater than in the case of EEG. Significant reduction of gIC and CSD spectral power depending on conditions was found in ADHD patients. Reducing power in a wide frequency range in the fronto-central areas is a common phenomenon regardless of whether the eyes were open or closed. Spectral power of local EEG activity isolated by gICA or CSD in the fronto-central areas may be a suitable marker for discrimination of ADHD and healthy adults. Spectral analysis of gIC and CSD provides better sensitivity to discriminate ADHD and healthy adults. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Snapshot hyperspectral imaging probe with principal component analysis and confidence ellipse for classification

NASA Astrophysics Data System (ADS)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2017-06-01

Hyperspectral imaging combines imaging and spectroscopy to provide detailed spectral information for each spatial point in the image. This gives a three-dimensional spatial-spatial-spectral datacube with hundreds of spectral images. Probe-based hyperspectral imaging systems have been developed so that they can be used in regions where conventional table-top platforms would find it difficult to access. A fiber bundle, which is made up of specially-arranged optical fibers, has recently been developed and integrated with a spectrograph-based hyperspectral imager. This forms a snapshot hyperspectral imaging probe, which is able to form a datacube using the information from each scan. Compared to the other configurations, which require sequential scanning to form a datacube, the snapshot configuration is preferred in real-time applications where motion artifacts and pixel misregistration can be minimized. Principal component analysis is a dimension-reducing technique that can be applied in hyperspectral imaging to convert the spectral information into uncorrelated variables known as principal components. A confidence ellipse can be used to define the region of each class in the principal component feature space and for classification. This paper demonstrates the use of the snapshot hyperspectral imaging probe to acquire data from samples of different colors. The spectral library of each sample was acquired and then analyzed using principal component analysis. Confidence ellipse was then applied to the principal components of each sample and used as the classification criteria. The results show that the applied analysis can be used to perform classification of the spectral data acquired using the snapshot hyperspectral imaging probe.

Spec Tool; an online education and research resource

NASA Astrophysics Data System (ADS)

Maman, S.; Shenfeld, A.; Isaacson, S.; Blumberg, D. G.

2016-06-01

Education and public outreach (EPO) activities related to remote sensing, space, planetary and geo-physics sciences have been developed widely in the Earth and Planetary Image Facility (EPIF) at Ben-Gurion University of the Negev, Israel. These programs aim to motivate the learning of geo-scientific and technologic disciplines. For over the past decade, the facility hosts research and outreach activities for researchers, local community, school pupils, students and educators. As software and data are neither available nor affordable, the EPIF Spec tool was created as a web-based resource to assist in initial spectral analysis as a need for researchers and students. The tool is used both in the academic courses and in the outreach education programs and enables a better understanding of the theoretical data of spectroscopy and Imaging Spectroscopy in a 'hands-on' activity. This tool is available online and provides spectra visualization tools and basic analysis algorithms including Spectral plotting, Spectral angle mapping and Linear Unmixing. The tool enables to visualize spectral signatures from the USGS spectral library and additional spectra collected in the EPIF such as of dunes in southern Israel and from Turkmenistan. For researchers and educators, the tool allows loading collected samples locally for further analysis.

The MIND PALACE: A Multi-Spectral Imaging and Spectroscopy Database for Planetary Science

NASA Astrophysics Data System (ADS)

Eshelman, E.; Doloboff, I.; Hara, E. K.; Uckert, K.; Sapers, H. M.; Abbey, W.; Beegle, L. W.; Bhartia, R.

2017-12-01

The Multi-Instrument Database (MIND) is the web-based home to a well-characterized set of analytical data collected by a suite of deep-UV fluorescence/Raman instruments built at the Jet Propulsion Laboratory (JPL). Samples derive from a growing body of planetary surface analogs, mineral and microbial standards, meteorites, spacecraft materials, and other astrobiologically relevant materials. In addition to deep-UV spectroscopy, datasets stored in MIND are obtained from a variety of analytical techniques obtained over multiple spatial and spectral scales including electron microscopy, optical microscopy, infrared spectroscopy, X-ray fluorescence, and direct fluorescence imaging. Multivariate statistical analysis techniques, primarily Principal Component Analysis (PCA), are used to guide interpretation of these large multi-analytical spectral datasets. Spatial co-referencing of integrated spectral/visual maps is performed using QGIS (geographic information system software). Georeferencing techniques transform individual instrument data maps into a layered co-registered data cube for analysis across spectral and spatial scales. The body of data in MIND is intended to serve as a permanent, reliable, and expanding database of deep-UV spectroscopy datasets generated by this unique suite of JPL-based instruments on samples of broad planetary science interest.

Breath analysis with broadly tunable quantum cascade lasers.

PubMed

Wörle, Katharina; Seichter, Felicia; Wilk, Andreas; Armacost, Chris; Day, Tim; Godejohann, Matthias; Wachter, Ulrich; Vogt, Josef; Radermacher, Peter; Mizaikoff, Boris

2013-03-05

With the availability of broadly tunable external cavity quantum cascade lasers (EC-QCLs), particularly bright mid-infrared (MIR; 3-20 μm) light sources are available offering high spectral brightness along with an analytically relevant spectral tuning range of >2 μm. Accurate isotope ratio determination of (12)CO2 and (13)CO2 in exhaled breath is of critical importance in the field of breath analysis, which may be addressed via measurements in the MIR spectral regime. Here, we combine for the first time an EC-QCL tunable across the (12)CO2/(13)CO2 spectral band with a miniaturized hollow waveguide gas cell for quantitatively determining the (12)CO2/(13)CO2 ratio within the exhaled breath of mice. Due to partially overlapping spectral features, these studies are augmented by appropriate multivariate data evaluation and calibration techniques based on partial least-squares regression along with optimized data preprocessing. Highly accurate determinations of the isotope ratio within breath samples collected from a mouse intensive care unit validated via hyphenated gas chromatography-mass spectrometry confirm the viability of IR-HWG-EC-QCL sensing techniques for isotope-selective exhaled breath analysis.

Fusion and quality analysis for remote sensing images using contourlet transform

NASA Astrophysics Data System (ADS)

Choi, Yoonsuk; Sharifahmadian, Ershad; Latifi, Shahram

2013-05-01

Recent developments in remote sensing technologies have provided various images with high spatial and spectral resolutions. However, multispectral images have low spatial resolution and panchromatic images have low spectral resolution. Therefore, image fusion techniques are necessary to improve the spatial resolution of spectral images by injecting spatial details of high-resolution panchromatic images. The objective of image fusion is to provide useful information by improving the spatial resolution and the spectral information of the original images. The fusion results can be utilized in various applications, such as military, medical imaging, and remote sensing. This paper addresses two issues in image fusion: i) image fusion method and ii) quality analysis of fusion results. First, a new contourlet-based image fusion method is presented, which is an improvement over the wavelet-based fusion. This fusion method is then applied to a case study to demonstrate its fusion performance. Fusion framework and scheme used in the study are discussed in detail. Second, quality analysis for the fusion results is discussed. We employed various quality metrics in order to analyze the fusion results both spatially and spectrally. Our results indicate that the proposed contourlet-based fusion method performs better than the conventional wavelet-based fusion methods.

The Impact of Quantitative Data Provided by a Multi-spectral Digital Skin Lesion Analysis Device on Dermatologists'Decisions to Biopsy Pigmented Lesions.

PubMed

Farberg, Aaron S; Winkelmann, Richard R; Tucker, Natalie; White, Richard; Rigel, Darrell S

2017-09-01

BACKGROUND: Early diagnosis of melanoma is critical to survival. New technologies, such as a multi-spectral digital skin lesion analysis (MSDSLA) device [MelaFind, STRATA Skin Sciences, Horsham, Pennsylvania] may be useful to enhance clinician evaluation of concerning pigmented skin lesions. Previous studies evaluated the effect of only the binary output. OBJECTIVE: The objective of this study was to determine how decisions dermatologists make regarding pigmented lesion biopsies are impacted by providing both the underlying classifier score (CS) and associated probability risk provided by multi-spectral digital skin lesion analysis. This outcome was also compared against the improvement reported with the provision of only the binary output. METHODS: Dermatologists attending an educational conference evaluated 50 pigmented lesions (25 melanomas and 25 benign lesions). Participants were asked if they would biopsy the lesion based on clinical images, and were asked this question again after being shown multi-spectral digital skin lesion analysis data that included the probability graphs and classifier score. RESULTS: Data were analyzed from a total of 160 United States board-certified dermatologists. Biopsy sensitivity for melanoma improved from 76 percent following clinical evaluation to 92 percent after quantitative multi-spectral digital skin lesion analysis information was provided ( p <0.0001). Specificity improved from 52 percent to 79 percent ( p <0.0001). The positive predictive value increased from 61 percent to 81 percent ( p <0.01) when the quantitative data were provided. Negative predictive value also increased (68% vs. 91%, p<0.01), and overall biopsy accuracy was greater with multi-spectral digital skin lesion analysis (64% vs. 86%, p <0.001). Interrater reliability improved (intraclass correlation 0.466 before, 0.559 after). CONCLUSION: Incorporating the classifier score and probability data into physician evaluation of pigmented lesions led to both increased sensitivity and specificity, thereby resulting in more accurate biopsy decisions.

Variables separation of the spectral BRDF for better understanding color variation in special effect pigment coatings.

PubMed

Ferrero, Alejandro; Rabal, Ana María; Campos, Joaquín; Pons, Alicia; Hernanz, María Luisa

2012-06-01

A type of representation of the spectral bidirectional reflectance distribution function (BRDF) is proposed that distinctly separates the spectral variable (wavelength) from the geometrical variables (spherical coordinates of the irradiation and viewing directions). Principal components analysis (PCA) is used in order to decompose the spectral BRDF in decorrelated spectral components, and the weight that they have at every geometrical configuration of irradiation/viewing is established. This method was applied to the spectral BRDF measurement of a special effect pigment sample, and four principal components with relevant variance were identified. These four components are enough to reproduce the great diversity of spectral reflectances observed at different geometrical configurations. Since this representation is able to separate spectral and geometrical variables, it facilitates the interpretation of the color variation of special effect pigments coatings versus the geometrical configuration of irradiation/viewing.

The Ring-Barking Experiment: Analysis of Forest Vitality Using Multi-Temporal Hyperspectral Data

NASA Astrophysics Data System (ADS)

Reichmuth, Anne; Bachmann, Martin; Heiden, Uta; Pinnel, Nicole; Holzwarth, Stefanie; Muller, Andreas; Henning, Lea; Einzmann, Kathrin; Immitzer, Markus; Seitz, Rudolf

2016-08-01

Through new operational optical spaceborne sensors (En- MAP and Sentinel-2) the impact analysis of climate change on forest ecosystems will be fostered. This analysis examines the potential of high spectral, spatial and temporal resolution data for detecting forest vegetation parameters, in particular Chlorophyll and Canopy Water content. The study site is a temperate spruce forest in Germany where in 2013 several trees were Ring-barked for a controlled die-off. During this experiment Ring- barked and Control trees were observed. Twelve airborne hyperspectral HySpex VNIR (Visible/Near Infrared) and SWIR (Shortwave Infrared) data with 1m spatial and 416 bands spectral resolution were acquired during the vegetation periods of 2013 and 2014. Additional laboratory spectral measurements of collected needle samples from Ring-barked and Control trees are available for needle level analysis. Index analysis of the laboratory measurements and image data are presented in this study.

Statistical analysis and machine learning algorithms for optical biopsy

NASA Astrophysics Data System (ADS)

Wu, Binlin; Liu, Cheng-hui; Boydston-White, Susie; Beckman, Hugh; Sriramoju, Vidyasagar; Sordillo, Laura; Zhang, Chunyuan; Zhang, Lin; Shi, Lingyan; Smith, Jason; Bailin, Jacob; Alfano, Robert R.

2018-02-01

Analyzing spectral or imaging data collected with various optical biopsy methods is often times difficult due to the complexity of the biological basis. Robust methods that can utilize the spectral or imaging data and detect the characteristic spectral or spatial signatures for different types of tissue is challenging but highly desired. In this study, we used various machine learning algorithms to analyze a spectral dataset acquired from human skin normal and cancerous tissue samples using resonance Raman spectroscopy with 532nm excitation. The algorithms including principal component analysis, nonnegative matrix factorization, and autoencoder artificial neural network are used to reduce dimension of the dataset and detect features. A support vector machine with a linear kernel is used to classify the normal tissue and cancerous tissue samples. The efficacies of the methods are compared.

Low Streamflow Forcasting using Minimum Relative Entropy

NASA Astrophysics Data System (ADS)

Cui, H.; Singh, V. P.

2013-12-01

Minimum relative entropy spectral analysis is derived in this study, and applied to forecast streamflow time series. Proposed method extends the autocorrelation in the manner that the relative entropy of underlying process is minimized so that time series data can be forecasted. Different prior estimation, such as uniform, exponential and Gaussian assumption, is taken to estimate the spectral density depending on the autocorrelation structure. Seasonal and nonseasonal low streamflow series obtained from Colorado River (Texas) under draught condition is successfully forecasted using proposed method. Minimum relative entropy determines spectral of low streamflow series with higher resolution than conventional method. Forecasted streamflow is compared to the prediction using Burg's maximum entropy spectral analysis (MESA) and Configurational entropy. The advantage and disadvantage of each method in forecasting low streamflow is discussed.

Site Characterization in the Urban Area of Tijuana, B. C., Mexico by Means of: H/V Spectral Ratios, Spectral Analysis of Surface Waves, and Random Decrement Method

NASA Astrophysics Data System (ADS)

Tapia-Herrera, R.; Huerta-Lopez, C. I.; Martinez-Cruzado, J. A.

2009-05-01

Results of site characterization for an experimental site in the metropolitan area of Tijuana, B. C., Mexico are presented as part of the on-going research in which time series of earthquakes, ambient noise, and induced vibrations were processed with three different methods: H/V spectral ratios, Spectral Analysis of Surface Waves (SASW), and the Random Decrement Method, (RDM). Forward modeling using the wave propagation stiffness matrix method (Roësset and Kausel, 1981) was used to compute the theoretical SH/P, SV/P spectral ratios, and the experimental H/V spectral ratios were computed following the conventional concepts of Fourier analysis. The modeling/comparison between the theoretical and experimental H/V spectral ratios was carried out. For the SASW method the theoretical dispersion curves were also computed and compared with the experimental one, and finally the theoretical free vibration decay curve was compared with the experimental one obtained with the RDM. All three methods were tested with ambient noise, induced vibrations, and earthquake signals. Both experimental spectral ratios obtained with ambient noise as well as earthquake signals agree quite well with the theoretical spectral ratios, particularly at the fundamental vibration frequency of the recording site. Differences between the fundamental vibration frequencies are evident for sites located at alluvial fill (~0.6 Hz) and at sites located at conglomerate/sandstones fill (0.75 Hz). Shear wave velocities for the soft soil layers of the 4-layer discrete soil model ranges as low as 100 m/s and up to 280 m/s. The results with the SASW provided information that allows to identify low velocity layers, not seen before with the traditional seismic methods. The damping estimations obtained with the RDM are within the expected values, and the dominant frequency of the system also obtained with the RDM correlates within the range of plus-minus 20 % with the one obtained by means of the H/V spectral ratio.

Applying horizontal diffusion on pressure surface to mesoscale models on terrain-following coordinates

Treesearch

Hann-Ming Henry Juang; Ching-Teng Lee; Yongxin Zhang; Yucheng Song; Ming-Chin Wu; Yi-Leng Chen; Kevin Kodama; Shyh-Chin Chen

2005-01-01

The National Centers for Environmental Prediction regional spectral model and mesoscale spectral model (NCEP RSM/MSM) use a spectral computation on perturbation. The perturbation is defined as a deviation between RSM/MSM forecast value and their outer model or analysis value on model sigma-coordinate surfaces. The horizontal diffusion used in the models applies...

Infrared spectral imaging as a novel approach for histopathological recognition in colon cancer diagnosis

NASA Astrophysics Data System (ADS)

Nallala, Jayakrupakar; Gobinet, Cyril; Diebold, Marie-Danièle; Untereiner, Valérie; Bouché, Olivier; Manfait, Michel; Sockalingum, Ganesh Dhruvananda; Piot, Olivier

2012-11-01

Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.

Wavelength Scanning with a Tilting Interference Filter for Glow-Discharge Elemental Imaging.

PubMed

Storey, Andrew P; Ray, Steven J; Hoffmann, Volker; Voronov, Maxim; Engelhard, Carsten; Buscher, Wolfgang; Hieftje, Gary M

2017-06-01

Glow discharges have long been used for depth profiling and bulk analysis of solid samples. In addition, over the past decade, several methods of obtaining lateral surface elemental distributions have been introduced, each with its own strengths and weaknesses. Challenges for each of these techniques are acceptable optical throughput and added instrumental complexity. Here, these problems are addressed with a tilting-filter instrument. A pulsed glow discharge is coupled to an optical system comprising an adjustable-angle tilting filter, collimating and imaging lenses, and a gated, intensified charge-coupled device (CCD) camera, which together provide surface elemental mapping of solid samples. The tilting-filter spectrometer is instrumentally simpler, produces less image distortion, and achieves higher optical throughput than a monochromator-based instrument, but has a much more limited tunable spectral range and poorer spectral resolution. As a result, the tilting-filter spectrometer is limited to single-element or two-element determinations, and only when the target spectral lines fall within an appropriate spectral range and can be spectrally discerned. Spectral interferences that result from heterogeneous impurities can be flagged and overcome by observing the spatially resolved signal response across the available tunable spectral range. The instrument has been characterized and evaluated for the spatially resolved analysis of glow-discharge emission from selected but representative samples.

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

Individual Sensitivity to Spectral and Temporal Cues in Listeners With Hearing Impairment

PubMed Central

Wright, Richard A.; Blackburn, Michael C.; Tatman, Rachael; Gallun, Frederick J.

2015-01-01

Purpose The present study was designed to evaluate use of spectral and temporal cues under conditions in which both types of cues were available. Method Participants included adults with normal hearing and hearing loss. We focused on 3 categories of speech cues: static spectral (spectral shape), dynamic spectral (formant change), and temporal (amplitude envelope). Spectral and/or temporal dimensions of synthetic speech were systematically manipulated along a continuum, and recognition was measured using the manipulated stimuli. Level was controlled to ensure cue audibility. Discriminant function analysis was used to determine to what degree spectral and temporal information contributed to the identification of each stimulus. Results Listeners with normal hearing were influenced to a greater extent by spectral cues for all stimuli. Listeners with hearing impairment generally utilized spectral cues when the information was static (spectral shape) but used temporal cues when the information was dynamic (formant transition). The relative use of spectral and temporal dimensions varied among individuals, especially among listeners with hearing loss. Conclusion Information about spectral and temporal cue use may aid in identifying listeners who rely to a greater extent on particular acoustic cues and applying that information toward therapeutic interventions. PMID:25629388

A Comparison of Raman Spectral Features of Frozen and Deparaffinized Tissues in Neuroblastoma and Ganglioneuroma

NASA Astrophysics Data System (ADS)

Devpura, Suneetha; Thakur, Jagdish S.; Poulik, Janet M.; Rabah, Raja; Naik, Vaman M.; Naik, Ratna

2012-02-01

We have investigated the cellular regions in neuroblastoma and ganglioneuroma using Raman spectroscopy and compared their spectral characteristics with those of normal adrenal gland. Thin sections from both frozen and deparaffinized tissues, obtained from the same tissue specimen, were studied in conjunction with the pathological examination of the tissues. We found a significant difference in the spectral features of frozen sections of normal adrenal gland, neuroblastoma, and ganglioneuroma when compared to deparaffinized tissues. The quantitative analysis of the Raman data using chemometric methods of principal component analysis and discriminant function analysis obtained from the frozen tissues show a sensitivity and specificity of 100% each. The biochemical identification based on the spectral differences shows that the normal adrenal gland tissues have higher levels of carotenoids, lipids, and cholesterol compared to the neuroblastoma and ganglioneuroma frozen tissues. However, deparaffinized tissues show complete removal of these biochemicals in adrenal tissues. This study demonstrates that Raman spectroscopy combined with chemometric methods can successfully distinguish neuroblastoma and ganglioneuroma at cellular level.

Analysis of Landsat-4 Thematic Mapper data for classification of forest stands in Baldwin County, Alabama

NASA Technical Reports Server (NTRS)

Hill, C. L.

1984-01-01

A computer-implemented classification has been derived from Landsat-4 Thematic Mapper data acquired over Baldwin County, Alabama on January 15, 1983. One set of spectral signatures was developed from the data by utilizing a 3x3 pixel sliding window approach. An analysis of the classification produced from this technique identified forested areas. Additional information regarding only the forested areas. Additional information regarding only the forested areas was extracted by employing a pixel-by-pixel signature development program which derived spectral statistics only for pixels within the forested land covers. The spectral statistics from both approaches were integrated and the data classified. This classification was evaluated by comparing the spectral classes produced from the data against corresponding ground verification polygons. This iterative data analysis technique resulted in an overall classification accuracy of 88.4 percent correct for slash pine, young pine, loblolly pine, natural pine, and mixed hardwood-pine. An accuracy assessment matrix has been produced for the classification.

A multimodal spectral approach to characterize rhythm in natural speech.

PubMed

Alexandrou, Anna Maria; Saarinen, Timo; Kujala, Jan; Salmelin, Riitta

2016-01-01

Human utterances demonstrate temporal patterning, also referred to as rhythm. While simple oromotor behaviors (e.g., chewing) feature a salient periodical structure, conversational speech displays a time-varying quasi-rhythmic pattern. Quantification of periodicity in speech is challenging. Unimodal spectral approaches have highlighted rhythmic aspects of speech. However, speech is a complex multimodal phenomenon that arises from the interplay of articulatory, respiratory, and vocal systems. The present study addressed the question of whether a multimodal spectral approach, in the form of coherence analysis between electromyographic (EMG) and acoustic signals, would allow one to characterize rhythm in natural speech more efficiently than a unimodal analysis. The main experimental task consisted of speech production at three speaking rates; a simple oromotor task served as control. The EMG-acoustic coherence emerged as a sensitive means of tracking speech rhythm, whereas spectral analysis of either EMG or acoustic amplitude envelope alone was less informative. Coherence metrics seem to distinguish and highlight rhythmic structure in natural speech.

Nonlinear single-spin spectrum analyzer.

PubMed

Kotler, Shlomi; Akerman, Nitzan; Glickman, Yinnon; Ozeri, Roee

2013-03-15

Qubits have been used as linear spectrum analyzers of their environments. Here we solve the problem of nonlinear spectral analysis, required for discrete noise induced by a strongly coupled environment. Our nonperturbative analytical model shows a nonlinear signal dependence on noise power, resulting in a spectral resolution beyond the Fourier limit as well as frequency mixing. We develop a noise characterization scheme adapted to this nonlinearity. We then apply it using a single trapped ion as a sensitive probe of strong, non-Gaussian, discrete magnetic field noise. Finally, we experimentally compared the performance of equidistant vs Uhrig modulation schemes for spectral analysis.

Channel Analysis for a 6.4 Gb s-1 DDR5 Data Buffer Receiver Front-End

NASA Astrophysics Data System (ADS)

Lehmann, Stefanie; Gerfers, Friedel

2017-09-01

In this contribution, the channel characteristic of the next generation DDR5-SDRAM architecture and possible approaches to overcome channel impairments are analysed. Because modern enterprise server applications and networks demand higher memory bandwidth, throughput and capacity, the DDR5-SDRAM specification is currently under development as a follow-up of DDR4-SDRAM technology. In this specification, the data rate is doubled to DDR5-6400 per IO as compared to the former DDR4-3200 architecture, resulting in a total per DIMM data rate of up to 409.6 Gb s-1. The single-ended multi-point-to-point CPU channel architecture in DDRX technology remains the same for DDR5 systems. At the specified target data rate, insertion loss, reflections, cross-talk as well as power supply noise become more severe and have to be considered. Using the data buffer receiver front-end of a load-reduced memory module, sophisticated equalisation techniques can be applied to ensure target BER at the increased data rate. In this work, the worst case CPU back-plane channel is analysed to derive requirements for receiver-side equalisation from the channel response characteristics. First, channel impairments such as inter-symbol-interference, reflections from the multi-point channel structure, and crosstalk from neighboring lines are analysed in detail. Based on these results, different correction methods for DDR5 data buffer front-ends are discussed. An architecture with 1-tap FFE in combination with a multi-tap DFE is proposed. Simulation of the architecture using a random input data stream is used to reveal the required DFE tap filter depth to effectively eliminate the dominant ISI and reflection based error components.

Forcing mechanism of the seasonally asymmetric quasi-biennial oscillation secondary circulation in ERA-40 and MAECHAM5

NASA Astrophysics Data System (ADS)

Peña-Ortiz, C.; Ribera, P.; García-Herrera, R.; Giorgetta, M. A.; García, R. R.

2008-08-01

The seasonality of the quasi-biennial oscillation (QBO) and its secondary circulation is analyzed in the European Reanalysis (ERA-40) and Middle Atmosphere European Centre Hamburg Model (MAECHAM5) general circulation model data sets through the multitaper method-singular value decomposition (MTM-SVD). In agreement with previous studies, the results reveal a strong seasonal dependence of the QBO secondary circulation. This is characterized by a two-cell structure symmetric about the equator during autumn and spring. However, anomalies strongly weaken in the summer hemisphere and strengthen in the winter hemisphere, leading to an asymmetric QBO secondary circulation characterized by a single-cell structure displaced into the winter hemisphere during the solstices. In ERA-40, this asymmetry is more pronounced during the northern than during the southern winter. These results provide the first observation of the QBO secondary circulation asymmetries in the ERA-40 reanalysis data set across the full stratosphere and the lower mesosphere, up to 0.1 hPa. The MTM-SVD reconstruction of the seasonal QBO signals in the residual circulation and the QBO signals in Eliassen Palm (EP) flux divergences suggest a particular mechanism for the seasonal asymmetries of the QBO secondary circulation and its extension across the midlatitudes. The analysis shows that the QBO modulates the EP flux in the winter hemispheric surf zone poleward of the QBO jets. The zonal wind forcing by EP flux divergence is transformed by the Coriolis effect into a meridional wind signal. The seasonality in the stratospheric EP flux and the hemispheric differences in planetary wave forcing cause the observed seasonality in the QBO secondary circulation and its hemispheric differences.

Altered modulation of gamma oscillation frequency by speed of visual motion in children with autism spectrum disorders.

PubMed

Stroganova, Tatiana A; Butorina, Anna V; Sysoeva, Olga V; Prokofyev, Andrey O; Nikolaeva, Anastasia Yu; Tsetlin, Marina M; Orekhova, Elena V

2015-01-01

Recent studies link autism spectrum disorders (ASD) with an altered balance between excitation and inhibition (E/I balance) in cortical networks. The brain oscillations in high gamma-band (50-120 Hz) are sensitive to the E/I balance and may appear useful biomarkers of certain ASD subtypes. The frequency of gamma oscillations is mediated by level of excitation of the fast-spiking inhibitory basket cells recruited by increasing strength of excitatory input. Therefore, the experimental manipulations affecting gamma frequency may throw light on inhibitory networks dysfunction in ASD. Here, we used magnetoencephalography (MEG) to investigate modulation of visual gamma oscillation frequency by speed of drifting annular gratings (1.2, 3.6, 6.0 °/s) in 21 boys with ASD and 26 typically developing boys aged 7-15 years. Multitaper method was used for analysis of spectra of gamma power change upon stimulus presentation and permutation test was applied for statistical comparisons. We also assessed in our participants visual orientation discrimination thresholds, which are thought to depend on excitability of inhibitory networks in the visual cortex. Although frequency of the oscillatory gamma response increased with increasing velocity of visual motion in both groups of participants, the velocity effect was reduced in a substantial proportion of children with ASD. The range of velocity-related gamma frequency modulation correlated inversely with the ability to discriminate oblique line orientation in the ASD group, while no such correlation has been observed in the group of typically developing participants. Our findings suggest that abnormal velocity-related gamma frequency modulation in ASD may constitute a potential biomarker for reduced excitability of fast-spiking inhibitory neurons in a subset of children with ASD.

WINDOWS: a program for the analysis of spectral data foil activation measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stallmann, F.W.; Eastham, J.F.; Kam, F.B.K.

The computer program WINDOWS together with its subroutines is described for the analysis of neutron spectral data foil activation measurements. In particular, the unfolding of the neutron differential spectrum, estimated windows and detector contributions, upper and lower bounds for an integral response, and group fluxes obtained from neutron transport calculations. 116 references. (JFP)

Water quality parameter measurement using spectral signatures

NASA Technical Reports Server (NTRS)

White, P. E.

1973-01-01

Regression analysis is applied to the problem of measuring water quality parameters from remote sensing spectral signature data. The equations necessary to perform regression analysis are presented and methods of testing the strength and reliability of a regression are described. An efficient algorithm for selecting an optimal subset of the independent variables available for a regression is also presented.

Skylab S-191 spectrometer single spectral scan analysis program. [user manual

NASA Technical Reports Server (NTRS)

Downes, E. L.

1974-01-01

Documentation and user information for the S-191 single spectral scan analysis program are reported. A breakdown of the computational algorithms is supplied, followed by the program listing and examples of sample output. A copy of the flow chart which describes the driver routine in the body of the main program segment is included.

Quantification of soil mapping by digital analysis of LANDSAT data. [Clinton County, Indiana

NASA Technical Reports Server (NTRS)

Kirschner, F. R.; Kaminsky, S. A.; Hinzel, E. J.; Sinclair, H. R.; Weismiller, R. A.

1977-01-01

Soil survey mapping units are designed such that the dominant soil represents the major proportion of the unit. At times, soil mapping delineations do not adequately represent conditions as stated in the mapping unit descriptions. Digital analysis of LANDSAT multispectral scanner (MSS) data provides a means of accurately describing and quantifying soil mapping unit composition. Digital analysis of LANDSAT MSS data collected on 9 June 1973 was used to prepare a spectral soil map for a 430-hectare area in Clinton County, Indiana. Fifteen spectral classes were defined, representing 12 soil and 3 vegetation classes. The 12 soil classes were grouped into 4 moisture regimes based upon their spectral responses; the 3 vegetation classes were grouped into one all-inclusive class.

[Analysis of H2S/PH3/NH3/AsH3/Cl2 by Full-Spectral Flame Photometric Detector].

PubMed

Ding, Zhi-jun; Wang, Pu-hong; Li, Zhi-jun; Du, Bin; Guo, Lei; Yu, Jian-hua

2015-07-01

Flame photometric analysis technology has been proven to be a rapid and sensitive method for sulfur and phosphorus detection. It has been widely used in environmental inspections, pesticide detection, industrial and agricultural production. By improving the design of the traditional flame photometric detector, using grating and CCD sensor array as a photoelectric conversion device, the types of compounds that can be detected were expanded. Instead of a single point of characteristic spectral lines, full spectral information has been used for qualitative and quantitative analysis of H2S, PH3, NH3, AsH3 and Cl2. Combined with chemometric method, flame photometric analysis technology is expected to become an alternative fast, real-time on-site detection technology to simultaneously detect multiple toxic and harmful gases.

Quasi-3-yr Cycle of Rainy Season Precipitation in Tibet Related to Different Types of ENSO during 1981-2015

NASA Astrophysics Data System (ADS)

Wang, Chunxue; Ma, Zhenfeng

2018-04-01

The rainy season precipitation in Tibet (RSPT) is a direct cause for local floods/droughts. It also indirectly affects the thermal conditions of the Tibetan Plateau, which can result in anomalous patterns of atmospheric circulation over East Asia. The interannual variability of the RSPT is often linked with the El Niño-Southern Oscillation (ENSO), but the relevant mechanisms are far from being understood, particularly for different types of ENSO events. We investigated the interannual variation of the RSPT in association with different types of ENSO. A quasi-3-yr period of the RSPT (less-more-more precipitation) was significant at the 95% confidence level. A joint multi-taper method with singular value decomposition analysis of the coupled field between the RSPT and the sea surface temperature (SST) revealed that the developing eastern Pacific type El Niño was accompanied by a decrease in the RSPT. The shift from the central Pacific type El Niño to the eastern Pacific La Niña was accompanied by an increase in the RSPT. Weakening of the central Pacific La Niña was accompanied by an increase in the RSPT. Analysis of the mechanism of this coupling, using the same analysis method but other climatic factors, indicated that the gradually strengthening eastern Pacific El Niño can inhibit the Walker circulation, weakening the South Asian summer monsoon, and resulting in transport of less water vapor from the Bay of Bengal to Tibet. The change from the central Pacific El Niño to the eastern Pacific La Niña led to continued strengthening of the Walker circulation with westward movement of the ascending area. This enhanced the South Asian summer monsoon over the Arabian Sea and transported more water vapor to Tibet. The decreasing central Pacific La Niña accompanied by persistent cooling of SSTs in the equatorial Pacific led to a strong eastern North Pacific summer monsoon, causing an anomaly in the easterly transport of water vapor from the Sea of Japan to Tibet and increased RSPT.

Three-stage Fabry-Perot liquid crystal tunable filter with extended spectral range.

PubMed

Zheng, Zhenrong; Yang, Guowei; Li, Haifeng; Liu, Xu

2011-01-31

A method to extend spectral range of tunable optical filter is proposed in this paper. Two same tunable Fabry-Perot filters and an additional tunable filter with different free spectral range are cascaded to extend spectral range and reduce sidelobes. Over 400 nm of free spectral range and 4 nm of full width at half maximum of the filter were achieved. Design procedure and simulation are described in detail. An experimental 3-stage tunable Fabry-Perot filter with visible and infrared spectra is demonstrated. The experimental results and the theoretical analysis are presented in detail to verify this method. The results revealed that a compact and extended tunable spectral range of Fabry-Perot filter can be easily attainable by this method.

A comparison of digital multi-spectral imagery versus conventional photography for mapping seagrass in Indian River Lagoon, Florida

DOE Office of Scientific and Technical Information (OSTI.GOV)

Virnstein, R.; Tepera, M.; Beazley, L.

1997-06-01

A pilot study is very briefly summarized in the article. The study tested the potential of multi-spectral digital imagery for discrimination of seagrass densities and species, algae, and bottom types. Imagery was obtained with the Compact Airborne Spectral Imager (casi) and two flight lines flown with hyper-spectral mode. The photogrammetric method used allowed interpretation of the highest quality product, eliminating limitations caused by outdated or poor quality base maps and the errors associated with transfer of polygons. Initial image analysis indicates that the multi-spectral imagery has several advantages, including sophisticated spectral signature recognition and classification, ease of geo-referencing, and rapidmore » mosaicking.« less

Solar Spectral Radiative Forcing Due to Dust Aerosol During the Puerto Rico Dust Experiment

NASA Technical Reports Server (NTRS)

Pilewskie, P.; Bergstrom, R.; Rabbette, M.; Livingston, J.; Russell, P.; Gore, Warren J. (Technical Monitor)

2000-01-01

During the Puerto Rico Dust Experiment (PRIDE) upwelling and downwelling solar spectral irradiance was measured on board the SPAWAR Navajo and downwelling solar spectral flux was measured at a surface site using the NASA Ames Solar Spectral Flux Radiometer. These data will be used to determine the net solar radiative forcing of dust aerosol and to quantify the solar spectral radiative energy budget in the presence of elevated aerosol loading. We will assess the variability in spectral irradiance using formal principal component analysis procedures and relate the radiative variability to aerosol microphysical properties. Finally, we will characterize the sea surface reflectance to improve aerosol optical depth retrievals from the AVHRR satellite and to validate SeaWiFS ocean color products.

Covariance propagation in spectral indices

DOE PAGES

Griffin, P. J.

2015-01-09

In this study, the dosimetry community has a history of using spectral indices to support neutron spectrum characterization and cross section validation efforts. An important aspect to this type of analysis is the proper consideration of the contribution of the spectrum uncertainty to the total uncertainty in calculated spectral indices (SIs). This study identifies deficiencies in the traditional treatment of the SI uncertainty, provides simple bounds to the spectral component in the SI uncertainty estimates, verifies that these estimates are reflected in actual applications, details a methodology that rigorously captures the spectral contribution to the uncertainty in the SI, andmore » provides quantified examples that demonstrate the importance of the proper treatment the spectral contribution to the uncertainty in the SI.« less

The continuum spectral characteristics of gamma-ray bursts observed by BATSE

NASA Technical Reports Server (NTRS)

Pendleton, Geoffrey N.; Paciesas, William S.; Briggs, Michael S.; Mallozzi, Robert S.; Koshut, Tom M.; Fishman, Gerald J.; Meegan, Charles A.; Wilson, Robert B.; Harmon, Alan B.; Kouveliotou, Chryssa

1994-01-01

Distributions of the continuum spectral characteristics of 260 bursts in the first Burst And Transient Source Experiement (BATSE) catalog are presented. The data are derived from flux calculated from BATSE Large Area Detector (LAD) four-channel discriminator data. The data are converted from counts to protons using a direct spectral inversion technique to remove the effects of atmospheric scattering and the energy dependence of the detector angular response. Although there are intriguing clusters of bursts in the spectral hardness ratio distributions, no evidence for the presence of distinct burst classes based in spectral hardness ratios alone is found. All subsets of bursts selected for their spectral characteristics in this analysis exhibit spatial distributions consistent with isotropy. The spectral diversity of the burst population appears to be caused largely by the highly variable nature of the burst production mechanisms themselves.

Direct measurement of group delay with joint time-frequency analysis of a white-light spectral interferogram.

PubMed

Deng, Yuqiang; Yang, Weijian; Zhou, Chun; Wang, Xi; Tao, Jun; Kong, Weipeng; Zhang, Zhigang

2008-12-01

We propose and demonstrate an analysis method to directly extract the group delay rather than the phase from the white-light spectral interferogram. By the joint time-frequency analysis technique, group delay is directly read from the ridge of wavelet transform, and group-delay dispersion is easily obtained by additional differentiation. The technique shows reasonable potential for the characterization of ultra-broadband chirped mirrors.

Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

PubMed

Knauer, Uwe; Matros, Andrea; Petrovic, Tijana; Zanker, Timothy; Scott, Eileen S; Seiffert, Udo

2017-01-01

Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples, perhaps due to colonized berries or sparse mycelia hidden within the bunch or airborne conidia on the berries that were detected by qPCR. An advanced approach to hyperspectral image classification based on combined spatial and spectral image features, potentially applicable to many available hyperspectral sensor technologies, has been developed and validated to improve the detection of powdery mildew infection levels of Chardonnay grape bunches. The spatial-spectral approach improved especially the detection of light infection levels compared with pixel-wise spectral data analysis. This approach is expected to improve the speed and accuracy of disease detection once the thresholds for fungal biomass detected by hyperspectral imaging are established; it can also facilitate monitoring in plant phenotyping of grapevine and additional crops.

Submillimeter, millimeter, and microwave spectral line catalogue

NASA Technical Reports Server (NTRS)

Poynter, R. L.; Pickett, H. M.

1980-01-01

A computer accessible catalogue of submillimeter, millimeter, and microwave spectral lines in the frequency range between O and 3000 GHz (such as; wavelengths longer than 100 m) is discussed. The catalogue was used as a planning guide and as an aid in the identification and analysis of observed spectral lines. The information listed for each spectral line includes the frequency and its estimated error, the intensity, lower state energy, and quantum number assignment. The catalogue was constructed by using theoretical least squares fits of published spectral lines to accepted molecular models. The associated predictions and their estimated errors are based upon the resultant fitted parameters and their covariances.

Azimuthally Anisotropic Global Adjoint Tomography

NASA Astrophysics Data System (ADS)

Bozdag, E.; Orsvuran, R.; Lefebvre, M. P.; Lei, W.; Peter, D. B.; Ruan, Y.; Smith, J. A.; Komatitsch, D.; Tromp, J.

2017-12-01

Earth's upper mantle shows significant evidence of anisotropy as a result of its composition and deformation. After the first-generation global adjoint tomography model, GLAD-M15 (Bozdag et al. 2016), which has transverse isotropy confined to upper mantle, we continue our iterations including surface-wave azimuthal anisotropy with an emphasis on the upper mantle. We are focusing on four elastic parameters that surface waves are known to be most sensitive to, namely, vertically and horizontally polarized shear waves and the density-normalised anisotropic parameters Gc' & Gs'. As part of the current anisotropic inversions, which will lead to our "second-generation" global adjoint tomography model, we have started exploring new misfits based on a double-difference approach (Yuan et al. 2016). We define our misfit function in terms of double-difference multitaper measurements, where each waveform is normalized by its number of pairs in the period ranges 45-100 s & 90-250 s. New measurements result in better balanced gradients while extracting more information underneath clusters of stations, such as USArray. Our initial results reveals multi-scale anisotorpic signals depending on ray (kernel) coverage close to continental-scale resolution in areas with dense coverage, consistent with previous studies.

Quasi-biennial modulation of the Northern Hemisphere tropopause height and temperature

NASA Astrophysics Data System (ADS)

Ribera, P.; PeñA-Ortiz, C.; AñEl, J. A.; Gimeno, L.; de la Torre, L.; Gallego, D.

2008-04-01

The influence of the quasi-biennial oscillation (QBO) on the tropopause pressure and temperature is studied through the application of the multitaper-singular value decomposition method (MTM-SVD). Reanalysis data (ERA-40) from the European Centre for Medium-Range Weather Forecasts (ECMWF) and radiosonde data from the Integrated Global Radiosonde Archive (IGRA) covering the period 1979-1999 are used. The results show a strong response of the height and temperature of the tropopause to the QBO not limited to the equatorial latitudes but affecting the entire Northern Hemisphere. A cooling (warming) of the tropopause temperature over polar (equatorial) latitudes during a QBO positive phase is observed, being particularly noticeable over polar latitudes. The anomalies in the tropopause height confirm these results, with the tropopause being at higher (lower) levels in polar (equatorial) latitudes during QBO positive phase. Results for the QBO negative phase are of opposite sign. We also found that the results obtained using raw radiosonde data and reanalysis are in very good agreement. Finally, the evolution of the mass stream function through a QBO cycle is used to justify the differences observed in the evolution of the tropopause characteristics at low and high latitudes through the QBO cycle.

Spectral analysis of crater central peak material (ccp)

NASA Astrophysics Data System (ADS)

Galiano, A.; Palomba, E.; Longobardo, A.; De Sanctis, M. C.; Raponi, A.; Tosi, F.; Ammannito, E.; Raymond, C. A.; Russell, C. T.

2017-09-01

We spectrally investigated 32 ccp units, which stand out in geologic maps of Ceres as they exhibit a different color and morphology with respect to the surrounding floor. We focus our attention on spectral parameters related to Mg-phyllosilicates (2.7 μm band), ammoniated phyllosilicates (3.1 μm band) and carbonates (bands at about 3.4 and 4.0 μm).

QEEG Spectral and Coherence Assessment of Autistic Children in Three Different Experimental Conditions

ERIC Educational Resources Information Center

Machado, Calixto; Estévez, Mario; Leisman, Gerry; Melillo, Robert; Rodríguez, Rafael; DeFina, Phillip; Hernández, Adrián; Pérez-Nellar, Jesús; Naranjo, Rolando; Chinchilla, Mauricio; Garófalo, Nicolás; Vargas, José; Beltrán, Carlos

2015-01-01

We studied autistics by quantitative EEG spectral and coherence analysis during three experimental conditions: basal, watching a cartoon with audio (V-A), and with muted audio band (VwA). Significant reductions were found for the absolute power spectral density (PSD) in the central region for delta and theta, and in the posterior region for sigma…

Cultural and environmental influences on temporal-spectral development patterns of corn and soybeans

NASA Technical Reports Server (NTRS)

Crist, E. P.

1982-01-01

A technique for evaluating crop temporal-spectral development patterns is described and applied to the analysis of cropping practices and environmental conditions as they affect reflectance characteristics of corn and soybean canopies. Typical variations in field conditions are shown to exert significant influences on the spectral development patterns, and thereby to affect the separability of the two crops.

Analysis of hyperspectral fluorescence images for poultry skin tumor inspection

NASA Astrophysics Data System (ADS)

Kong, Seong G.; Chen, Yud-Ren; Kim, Intaek; Kim, Moon S.

2004-02-01

We present a hyperspectral fluorescence imaging system with a fuzzy inference scheme for detecting skin tumors on poultry carcasses. Hyperspectral images reveal spatial and spectral information useful for finding pathological lesions or contaminants on agricultural products. Skin tumors are not obvious because the visual signature appears as a shape distortion rather than a discoloration. Fluorescence imaging allows the visualization of poultry skin tumors more easily than reflectance. The hyperspectral image samples obtained for this poultry tumor inspection contain 65 spectral bands of fluorescence in the visible region of the spectrum at wavelengths ranging from 425 to 711 nm. The large amount of hyperspectral image data is compressed by use of a discrete wavelet transform in the spatial domain. Principal-component analysis provides an effective compressed representation of the spectral signal of each pixel in the spectral domain. A small number of significant features are extracted from two major spectral peaks of relative fluorescence intensity that have been identified as meaningful spectral bands for detecting tumors. A fuzzy inference scheme that uses a small number of fuzzy rules and Gaussian membership functions successfully detects skin tumors on poultry carcasses. Spatial-filtering techniques are used to significantly reduce false positives.

Spectral imaging of histological and cytological specimens

NASA Astrophysics Data System (ADS)

Rothmann, Chana; Malik, Zvi

1999-05-01

Evaluation of cell morphology by bright field microscopy is the pillar of histopathological diagnosis. The need for quantitative and objective parameters for diagnosis has given rise to the development of morphometric methods. The development of spectral imaging for biological and medical applications introduced both fields to large amounts of information extracted from a single image. Spectroscopic analysis is based on the ability of a stained histological specimen to absorb, reflect, or emit photons in ways characteristic to its interactions with specific dyes. Spectral information obtained from a histological specimen is stored in a cube whose appellate signifies the two spatial dimensions of a flat sample (x and y) and the third dimension, the spectrum, representing the light intensity for every wavelength. The spectral information stored in the cube can be further processed by morphometric analysis and quantitative procedures. Such a procedure is spectral-similarity mapping (SSM), which enables the demarcation of areas occupied by the same type of material. SSM constructs new images of the specimen, revealing areas with similar stain-macromolecule characteristics and enhancing subcellular features. Spectral imaging combined with SSM reveals nuclear organization through the differentiation stages as well as in apoptotic and necrotic conditions and identifies specifically the nucleoli domains.

Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks*

PubMed Central

Bandeira, Nuno

2016-01-01

Peptide and protein identification remains challenging in organisms with poorly annotated or rapidly evolving genomes, as are commonly encountered in environmental or biofuels research. Such limitations render tandem mass spectrometry (MS/MS) database search algorithms ineffective as they lack corresponding sequences required for peptide-spectrum matching. We address this challenge with the spectral networks approach to (1) match spectra of orthologous peptides across multiple related species and then (2) propagate peptide annotations from identified to unidentified spectra. We here present algorithms to assess the statistical significance of spectral alignments (Align-GF), reduce the impurity in spectral networks, and accurately estimate the error rate in propagated identifications. Analyzing three related Cyanothece species, a model organism for biohydrogen production, spectral networks identified peptides from highly divergent sequences from networks with dozens of variant peptides, including thousands of peptides in species lacking a sequenced genome. Our analysis further detected the presence of many novel putative peptides even in genomically characterized species, thus suggesting the possibility of gaps in our understanding of their proteomic and genomic expression. A web-based pipeline for spectral networks analysis is available at http://proteomics.ucsd.edu/software. PMID:27609420

[The design and implementation of the web typical surface object spectral information system in arid areas based on .NET and SuperMap].

PubMed

Xia, Jun; Tashpolat, Tiyip; Zhang, Fei; Ji, Hong-jiang

2011-07-01

The characteristic of object spectrum is not only the base of the quantification analysis of remote sensing, but also the main content of the basic research of remote sensing. The typical surface object spectral database in arid areas oasis is of great significance for applied research on remote sensing in soil salinization. In the present paper, the authors took the Ugan-Kuqa River Delta Oasis as an example, unified .NET and the SuperMap platform with SQL Server database stored data, used the B/S pattern and the C# language to design and develop the typical surface object spectral information system, and established the typical surface object spectral database according to the characteristics of arid areas oasis. The system implemented the classified storage and the management of typical surface object spectral information and the related attribute data of the study areas; this system also implemented visualized two-way query between the maps and attribute data, the drawings of the surface object spectral response curves and the processing of the derivative spectral data and its drawings. In addition, the system initially possessed a simple spectral data mining and analysis capabilities, and this advantage provided an efficient, reliable and convenient data management and application platform for the Ugan-Kuqa River Delta Oasis's follow-up study in soil salinization. Finally, It's easy to maintain, convinient for secondary development and practically operating in good condition.

Effects of Salinity on Leaf Spectral Reflectance and Biochemical Parameters of Nitrogen Fixing Soybean Plants (Glycine max L.)

NASA Astrophysics Data System (ADS)

Krezhova, Dora D.; Kirova, Elisaveta B.; Yanev, Tony K.; Iliev, Ilko Ts.

2010-01-01

Measurements of physiology and hyperspectral leaf reflectance were used to detect salinity stress in nitrogen fixing soybean plants. Seedlings were inoculated with suspension of Bradyrhizobium japonicum strain 273. Salinity was performed at the stage of 2nd-4th trifoliate expanded leaves by adding of NaCl in the nutrient solution of Helrigel in concentrations 40 mM and 80 mM. A comparative analysis was performed between the changes in the biochemical parameters - stress markers (phenols, proline, malondialdehyde, thiol groups), chlorophyll a and b, hydrogen peroxide, and leaf spectral reflectance in the spectral range 450-850 nm. The spectral measurements were carried out by an USB2000 spectrometer. The reflectance data of the control and treated plants in the red, green, red-edge and the near infrared ranges of the spectrum were subjected to statistical analysis. Statistically significant differences were found through the Student's t-criterion at the two NaCl concentrations in all of the ranges examined with the exception of the near infrared range at 40 mM NaCl concentration. Similar results were obtained through linear discriminant analysis. The tents of the phenols, malondialdehyde and chlorophyll a and b were found to decrease at both salinity treatments. In the spectral data this effect is manifested by decrease of the reflectance values in the green and red ranges. The contents of proline, hydrogen peroxide and thiol groups rose with the NaCl concentration increase. At 80 mM NaCl concentration the values of these markers showed a considerable increase giving evidence that the soybean plants were stressed in comparison with the control. This finding is in agreement with the results from the spectral reflectance analysis.

Distribution of CO2 in Saturn's Atmosphere from Cassini/cirs Infrared Observations

NASA Astrophysics Data System (ADS)

Abbas, M. M.; LeClair, A.; Woodard, E.; Young, M.; Stanbro, M.; Flasar, F. M.; Kunde, V. G.; Achterberg, R. K.; Bjoraker, G.; Brasunas, J.; Jennings, D. E.; the Cassini/CIRS Team

2013-10-01

This paper focuses on the CO2 distribution in Saturn's atmosphere based on analysis of infrared spectral observations of Saturn made by the Composite Infrared Spectrometer aboard the Cassini spacecraft. The Cassini spacecraft was launched in 1997 October, inserted in Saturn's orbit in 2004 July, and has been successfully making infrared observations of Saturn, its rings, Titan, and other icy satellites during well-planned orbital tours. The infrared observations, made with a dual Fourier transform spectrometer in both nadir- and limb-viewing modes, cover spectral regions of 10-1400 cm-1, with the option of variable apodized spectral resolutions from 0.53 to 15 cm-1. An analysis of the observed spectra with well-developed radiative transfer models and spectral inversion techniques has the potential to provide knowledge of Saturn's thermal structure and composition with global distributions of a series of gases. In this paper, we present an analysis of a large observational data set for retrieval of Saturn's CO2 distribution utilizing spectral features of CO2 in the Q-branch of the ν2 band, and discuss its possible relationship to the influx of interstellar dust grains. With limited spectral regions available for analysis, due to low densities of CO2 and interference from other gases, the retrieved CO2 profile is obtained as a function of a model photochemical profile, with the retrieved values at atmospheric pressures in the region of ~1-10 mbar levels. The retrieved CO2 profile is found to be in good agreement with the model profile based on Infrared Space Observatory measurements with mixing ratios of ~4.9 × 10-10 at atmospheric pressures of ~1 mbar.

Non-Invasive Survey of Old Paintings Using Vnir Hyperspectral Sensor

NASA Astrophysics Data System (ADS)

Matouskova, E.; Pavelka, K.; Svadlenkova, Z.

2013-07-01

Hyperspectral imaging is relatively new method developed primarily for army applications with respect to detection of possible chemical weapon existence and as an efficient assistant for a geological survey. The method is based on recording spectral profile for many hundreds of narrow spectral band. The technique gives full spectral curve of explored pixel which is an unparalleled signature of pixels material. Spectral signatures can then be compared with pre-defined spectral libraries or they can be created with respect to application. A new project named "New Modern Methods of Non-invasive Survey of Historical Site Objects" started at CTU in Prague with the New Year. The project is designed for 4 years and is funded by the Ministry of Culture in the Czech Republic. It is focused on material and chemical composition, damage diagnostics, condition description of paintings, images, construction components and whole structure object analysis in cultural heritage domain. This paper shows first results of the project on painting documentation field as well as used instrument. Hyperspec VNIR by Headwall Photonics was used for this analysis. It operates in the spectral range between 400 and 1000 nm. Comparison with infrared photography is discussed. The goal of this contribution is a non-destructive deep exploration of specific paintings. Two original 17th century paintings by Flemish authors Thomas van Apshoven ("On the Road") and David Teniers the Younger ("The Interior of a Mill") were chosen for the first analysis with a kind permission of academic painter Mr. M. Martan. Both paintings oil painted on wooden panel. This combination was chosen because of the possibility of underdrawing visualization which is supposed to be the most uncomplicated painting combination for this type of analysis.

Possible shift in the ENSO-Indian monsoon rainfall relationship under future global warming

PubMed Central

Azad, Sarita; Rajeevan, M.

2016-01-01

EI Nino-Southern Oscillation (ENSO) and Indian monsoon rainfall are known to have an inverse relationship, which we have observed in the rainfall spectrum exhibiting a spectral dip in 3–5 y period band. It is well documented that El Nino events are known to be associated with deficit rainfall. Our analysis reveals that this spectral dip (3–5 y) is likely to shift to shorter periods (2.5–3 y) in future, suggesting a possible shift in the relationship between ENSO and monsoon rainfall. Spectral analysis of future climate projections by 20 Coupled Model Intercomparison project 5 (CMIP5) models are employed in order to corroborate our findings. Change in spectral dip speculates early occurrence of drought events in future due to multiple factors of global warming. PMID:26837459

Neural networks using broadband spectral discriminators reduces illumination required for broccoli identification in weedy fields

NASA Astrophysics Data System (ADS)

Hahn, Federico

1996-03-01

Statistical discriminative analysis and neural networks were used to prove that crop/weed/soil discrimination by optical reflectance was feasible. The wavelengths selected as inputs on those neural networks were ten nanometers width, reducing the total collected radiation for the sensor. Spectral data collected from several farms having different weed populations were introduced to discriminant analysis. The best discriminant wavelengths were used to build a wavelength histogram which selected the three best spectral broadbands for broccoli/weed/soil discrimination. The broadbands were analyzed using a new single broadband discriminator index named the discriminative integration index, DII, and the DII values obtained were used to train a neural network. This paper introduces the index concept, its results and its use for minimizing artificial lightning requirements with broadband spectral measurements for broccoli/weed/soil discrimination.

Label-free observation of tissues by high-speed stimulated Raman spectral microscopy and independent component analysis

NASA Astrophysics Data System (ADS)

Ozeki, Yasuyuki; Otsuka, Yoichi; Sato, Shuya; Hashimoto, Hiroyuki; Umemura, Wataru; Sumimura, Kazuhiko; Nishizawa, Norihiko; Fukui, Kiichi; Itoh, Kazuyoshi

2013-02-01

We have developed a video-rate stimulated Raman scattering (SRS) microscope with frame-by-frame wavenumber tunability. The system uses a 76-MHz picosecond Ti:sapphire laser and a subharmonically synchronized, 38-MHz Yb fiber laser. The Yb fiber laser pulses are spectrally sliced by a fast wavelength-tunable filter, which consists of a galvanometer scanner, a 4-f optical system and a reflective grating. The spectral resolution of the filter is ~ 3 cm-1. The wavenumber was scanned from 2800 to 3100 cm-1 with an arbitrary waveform synchronized to the frame trigger. For imaging, we introduced a 8-kHz resonant scanner and a galvanometer scanner. We were able to acquire SRS images of 500 x 480 pixels at a frame rate of 30.8 frames/s. Then these images were processed by principal component analysis followed by a modified algorithm of independent component analysis. This algorithm allows blind separation of constituents with overlapping Raman bands from SRS spectral images. The independent component (IC) spectra give spectroscopic information, and IC images can be used to produce pseudo-color images. We demonstrate various label-free imaging modalities such as 2D spectral imaging of the rat liver, two-color 3D imaging of a vessel in the rat liver, and spectral imaging of several sections of intestinal villi in the mouse. Various structures in the tissues such as lipid droplets, cytoplasm, fibrous texture, nucleus, and water-rich region were successfully visualized.

A Study on Spectral Signature Analysis of Wetland Vegetation Based on Ground Imaging Spectrum Data

NASA Astrophysics Data System (ADS)

Ling, Chengxing; Liu, Hua; Ju, Hongbo; Zhang, Huaiqing; You, Jia; Li, Weina

2017-10-01

The objective of this study was to verify the application of imaging spectrometer in wetland vegetation remote sensing monitoring, based on analysis of wetland vegetation spectral features. Spectral information of Carex vegetation spectral data under different water environment was collected bySOC710VP and ASD FieldSpec 3; Meanwhile, the chlorophyll contents of wheat leaves were tested in the lab. A total 9 typical vegetation indices were calculated by using two instruments’ data which were spectral values from 400nm to 1000 nm. Then features between the same vegetation indices and soil water contents for two applications were analyzed and compared. The results showed that there were same spectrum curve trends of Carex vegetation (soil moisture content of 51%, 32%, 14% and three regional comparative analysis)reflectance between SOC710VP and ASD FieldSpec 3, including the two reflectance peak of 550nm and 730 nm, two reflectance valley of 690 nm and 970nm, and continuous near infrared reflectance platform. However, The two also have a very clear distinction: (1) The reflection spectra of SOC710VP leaves of Carex Carex leaf spectra in the three soil moisture environment values are greater than ASD FieldSpec 3 collected value; (2) The SOC710VP reflectivity curve does not have the smooth curve of the original spectrum measured by the ASD FieldSpec 3, the amplitude of fluctuation is bigger, and it is more obvious in the near infrared band. It is concluded that SOC710VP spectral data are reliable, with the image features, spectral curve features reliable. It has great potential in the research of hyperspectral remote sensing technology in the development of wetland near earth, remote sensing monitoring of wetland resources.

Does the Blazar Gamma-ray Spectrum Harden with Increasing Flux? - Analysis of Nine Years of EGRET Data

NASA Technical Reports Server (NTRS)

Nandikotkur, Giridhar; Jahoda, Keith M.; Hartman, R. C.; Mukherjee, R.; Sreekumar, P.; Boettcher, M.

2007-01-01

The Energetic Gamma Ray Experiment Telescope (EGRET) on the Compton Gamma Ray Observatory (CGRO) discovered gamma-ray emission from more than 67 blazars during its nine-year lifetime. We conducted an exhaustive search of the EGRET archives and selected all the blazars that were observed multiple times and were bright enough to enable a spectral analysis using standard powerlaw models. The sample consists of 18 flat-spectrum radio quasars (FSRQs), 6 low-frequency-peaked BL Lacs (LBLs) and 2 high-frequency-peaked BL Lacs (HBLs). We do not detect any clear pattern in'the variation of spectral index with flux. Some of the blazars do not show any statistical evidence for spectral variability. The spectrum hardens with increasing flux in a few cases. There is also evidence for a flux-hardness anticorrelation at lo\\v fluxes in five blazars. The well observed blazars (3C 279,3C 273, PKS 0528-i-134, PKS 1622-297, PKS 0208- 512) do not show any overall trend in the long-term spectral dependence on flux, but the sample shows a mixture of hard and soft states. We observed spectral hysteresis at weekly timescales in all the three FSRQs for which data from flares lasting for 3 approx. 4 weeks were available. All three sources show a counterclockwise rotation despite the widely different flux profiles. Hysteresis in the spectral index vs. flux space has never been observed in FSRQs in gamma-rays at weekly timescales. itre analyze the observed spectral behavior in the context of various inverse-Compton mechanisms believed to be responsible for emission in the EGRET energy range. Our analysis uses the EGRET skymaps that were regenerated to include the changes in performance during the mission.

A novel approach to pharmaco-EEG for investigating analgesics: assessment of spectral indices in single-sweep evoked brain potentials.

PubMed

Gram, Mikkel; Graversen, Carina; Nielsen, Anders K; Arendt-Nielsen, Thomas; Mørch, Carsten D; Andresen, Trine; Drewes, Asbjørn M

2013-12-01

To compare results from analysis of averaged and single-sweep evoked brain potentials (EPs) by visual inspection and spectral analysis in order to identify an objective measure for the analgesic effect of buprenorphine and fentanyl. Twenty-two healthy males were included in a randomized study to assess the changes in EPs after 110 sweeps of painful electrical stimulation to the median nerve following treatment with buprenorphine, fentanyl or placebo patches. Bone pressure, cutaneous heat and electrical pain ratings were assessed. EPs and pain assessments were obtained before drug administration, 24, 48, 72 and 144 h after beginning of treatment. Features from EPs were extracted by three different approaches: (i) visual inspection of amplitude and latency of the main peaks in the average EPs, (ii) spectral distribution of the average EPs and (iii) spectral distribution of the EPs from single-sweeps. Visual inspection revealed no difference between active treatments and placebo (all P > 0.05). Spectral distribution of the averaged potentials showed a decrease in the beta (12-32 Hz) band for fentanyl (P = 0.036), which however did not correlate with pain ratings. Spectral distribution in the single-sweep EPs revealed significant increases in the theta, alpha and beta bands for buprenorphine (all P < 0.05) as well as theta band increase for fentanyl (P = 0.05). For buprenorphine, beta band activity correlated with bone pressure and cutaneous heat pain (both P = 0.04, r = 0.90). In conclusion single-sweep spectral band analysis increases the information on the response of the brain to opioids and may be used to identify the response to analgesics. © 2013 The Authors. British Journal of Clinical Pharmacology © 2013 The British Pharmacological Society.

MIR and FIR Analysis of Inorganic Species in a Single Data Acquisition

NASA Astrophysics Data System (ADS)

Wang, Peng; Shilov, Sergey

2017-06-01

The extension of the mid IR towards the far IR spectral range below 400 \\wn is of great interest for molecular vibrational analysis for inorganic and organometallic chemistry, for geological, pharmaceutical, and physical applications, polymorph screening and crystallinity analysis as well as for matrix isolation spectroscopy. In these cases, the additional far infrared region offers insight to low energy vibrations which are observable only there. This includes inorganic species, lattice vibrations or intermolecular vibrations in the ordered solid state. The spectral range of a FTIR spectrometer is defined by the major optical components such as the source, beamsplitter, and detector. The globar source covers a broad spectral range from 8000 to 20 \\wn. However a bottle neck exists with respect to the beamsplitter and detector. To extend the spectral range further into the far IR and THz spectral ranges, one or more additional far IR beam splitters and detectors have been previously required. Two new optic components have been incorporated in a spectrometer to achieve coverage of both the mid and far infrared in a single scan: a wide range MIR-FIR beam splitter and the wide range DLaTGS detector that utilizes a diamond window. The use of a standard SiC IR source with these components yields a spectral range of 6000 down to 50 \\wn in one step for all types of transmittance, reflectance and ATR measurements. Utilizing the external water cooled mercury arc high power lamp the spectral range can be ultimately extended down to 10 \\wn. Examples of application will include emission in MIR-THz range, identification of pigments, additives in polymers, and polymorphism studies.

Assessment of insulin sensitivity by the hyperinsulinemic euglycemic clamp: Comparison with the spectral analysis of photoplethysmography.

PubMed

De Souza, Aglecio Luiz; Batista, Gisele Almeida; Alegre, Sarah Monte

2017-01-01

We compare spectral analysis of photoplethysmography (PTG) with insulin resistance measured by the hyperinsulinemic euglycemic clamp (HEC) technique. A total of 100 nondiabetic subjects, 43 men and 57 women aged 20-63years, 30 lean, 42 overweight and 28 obese were enrolled in the study. These patients underwent an examination with HEC, and an examination with the PTG spectral analysis and calculation of the PTG Total Power (PTG-TP). Receiver-operating characteristic (ROC) curves were constructed to determine the specificity and sensitivity of PTG-TP in the assessment of insulin resistance. There is a moderate correlation between insulin sensitivity (M-value) and PTG-TP (r=- 0.64, p<0.0001). The ROC curves showed that the most relevant cutoff to the whole study group was a PTG-TP>406.2. This cut-off had a sensitivity=95.7%, specificity =84,4% and the area under the ROC curve (AUC)=0.929 for identifying insulin resistance. All AUC ROC curve analysis were significant (p<0.0001). The use of the PTG-TP marker measured from the PTG spectral analysis is a useful tool in screening and follow up of IR, especially in large-scale studies. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

High-speed vibrational imaging and spectral analysis of lipid bodies by compound Raman microscopy.

PubMed

Slipchenko, Mikhail N; Le, Thuc T; Chen, Hongtao; Cheng, Ji-Xin

2009-05-28

Cells store excess energy in the form of cytoplasmic lipid droplets. At present, it is unclear how different types of fatty acids contribute to the formation of lipid droplets. We describe a compound Raman microscope capable of both high-speed chemical imaging and quantitative spectral analysis on the same platform. We used a picosecond laser source to perform coherent Raman scattering imaging of a biological sample and confocal Raman spectral analysis at points of interest. The potential of the compound Raman microscope was evaluated on lipid bodies of cultured cells and live animals. Our data indicate that the in vivo fat contains much more unsaturated fatty acids (FAs) than the fat formed via de novo synthesis in 3T3-L1 cells. Furthermore, in vivo analysis of subcutaneous adipocytes and glands revealed a dramatic difference not only in the unsaturation level but also in the thermodynamic state of FAs inside their lipid bodies. Additionally, the compound Raman microscope allows tracking of the cellular uptake of a specific fatty acid and its abundance in nascent cytoplasmic lipid droplets. The high-speed vibrational imaging and spectral analysis capability renders compound Raman microscopy an indispensible analytical tool for the study of lipid-droplet biology.

Pretreatment and integrated analysis of spectral data reveal seaweed similarities based on chemical diversity.

PubMed

Wei, Feifei; Ito, Kengo; Sakata, Kenji; Date, Yasuhiro; Kikuchi, Jun

2015-03-03

Extracting useful information from high dimensionality and large data sets is a major challenge for data-driven approaches. The present study was aimed at developing novel integrated analytical strategies for comprehensively characterizing seaweed similarities based on chemical diversity. The chemical compositions of 107 seaweed and 2 seagrass samples were analyzed using multiple techniques, including Fourier transform infrared (FT-IR) and solid- and solution-state nuclear magnetic resonance (NMR) spectroscopy, thermogravimetry-differential thermal analysis (TG-DTA), inductively coupled plasma-optical emission spectrometry (ICP-OES), CHNS/O total elemental analysis, and isotope ratio mass spectrometry (IR-MS). The spectral data were preprocessed using non-negative matrix factorization (NMF) and NMF combined with multivariate curve resolution-alternating least-squares (MCR-ALS) methods in order to separate individual component information from the overlapping and/or broad spectral peaks. Integrated analysis of the preprocessed chemical data demonstrated distinct discrimination of differential seaweed species. Further network analysis revealed a close correlation between the heavy metal elements and characteristic components of brown algae, such as cellulose, alginic acid, and sulfated mucopolysaccharides, providing a componential basis for its metal-sorbing potential. These results suggest that this integrated analytical strategy is useful for extracting and identifying the chemical characteristics of diverse seaweeds based on large chemical data sets, particularly complicated overlapping spectral data.

Spectral Analysis of Word-Initial Alveolar and Velar Plosives Produced by Iranian Children with Cleft Lip and Palate

ERIC Educational Resources Information Center

Eshghi, Marziye; Zajac, David J.; Bijankhan, Mahmood; Shirazi, Mohsen

2013-01-01

Spectral moment analysis (SMA) was used to describe voiceless alveolar and velar stop-plosive production in Persian-speaking children with repaired cleft lip and palate (CLP). Participants included 11 children with bilateral CLP who were undergoing maxillary expansion and 20 children without any type of orofacial clefts. Four of the children with…

Spectral analysis using CCDs

NASA Technical Reports Server (NTRS)

Hewes, C. R.; Brodersen, R. W.; De Wit, M.; Buss, D. D.

1976-01-01

Charge-coupled devices (CCDs) are ideally suited for performing sampled-data transversal filtering operations in the analog domain. Two algorithms have been identified for performing spectral analysis in which the bulk of the computation can be performed in a CCD transversal filter; the chirp z-transform and the prime transform. CCD implementation of both these transform algorithms is presented together with performance data and applications.

Mapping asphalt pavement aging and condition using multiple endmember spectral mixture analysis in Beijing, China

NASA Astrophysics Data System (ADS)

Pan, Yifan; Zhang, Xianfeng; Tian, Jie; Jin, Xu; Luo, Lun; Yang, Ke

2017-01-01

Asphalt road reflectance spectra change as pavement ages. This provides the possibility for remote sensing to be used to monitor a change in asphalt pavement conditions. However, the relatively narrow geometry of roads and the relatively coarse spatial resolution of remotely sensed imagery result in mixtures between pavement and adjacent landcovers (e.g., vegetation, buildings, and soil), increasing uncertainties in spectral analysis. To overcome this problem, multiple endmember spectral mixture analysis (MESMA) was used to map the asphalt pavement condition using Worldview-2 satellite imagery in this study. Based on extensive field investigation and in situ measurements, aged asphalt pavements were categorized into four stages-preliminarily aged, moderately aged, heavily aged, and distressed. The spectral characteristics in the first three stages were further analyzed, and a MESMA unmixing analysis was conducted to map these three kinds of pavement conditions from the Worldview-2 image. The results showed that the road pavement conditions could be detected well and mapped with an overall accuracy of 81.71% and Kappa coefficient of 0.77. Finally, a quantitative assessment of the pavement conditions for each road segment in this study area was conducted to inform road maintenance management.

A two-step along-track spectral analysis for estimating the magnetic signals of magnetospheric ring current from Swarm data

NASA Astrophysics Data System (ADS)

Martinec, Zdeněk; Velímský, Jakub; Haagmans, Roger; Šachl, Libor

2018-02-01

This study deals with the analysis of Swarm vector magnetic field measurements in order to estimate the magnetic field of magnetospheric ring current. For a single Swarm satellite, the magnetic measurements are processed by along-track spectral analysis on a track-by-track basis. The main and lithospheric magnetic fields are modelled by the CHAOS-6 field model and subtracted from the along-track Swarm magnetic data. The mid-latitude residual signal is then spectrally analysed and extrapolated to the polar regions. The resulting model of the magnetosphere (model MME) is compared to the existing Swarm Level 2 magnetospheric field model (MMA_SHA_2C). The differences of up to 10 nT are found on the nightsides Swarm data from 2014 April 8 to May 10, which are due to different processing schemes used to construct the two magnetospheric magnetic field models. The forward-simulated magnetospheric magnetic field generated by the external part of model MME then demonstrates the consistency of the separation of the Swarm along-track signal into the external and internal parts by the two-step along-track spectral analysis.

Distinguishing low frequency oscillations within the 1/f spectral behaviour of electromagnetic brain signals.

PubMed

Demanuele, Charmaine; James, Christopher J; Sonuga-Barke, Edmund Js

2007-12-10

It has been acknowledged that the frequency spectrum of measured electromagnetic (EM) brain signals shows a decrease in power with increasing frequency. This spectral behaviour may lead to difficulty in distinguishing event-related peaks from ongoing brain activity in the electro- and magnetoencephalographic (EEG and MEG) signal spectra. This can become an issue especially in the analysis of low frequency oscillations (LFOs) - below 0.5 Hz - which are currently being observed in signal recordings linked with specific pathologies such as epileptic seizures or attention deficit hyperactivity disorder (ADHD), in sleep studies, etc. In this work we propose a simple method that can be used to compensate for this 1/f trend hence achieving spectral normalisation. This method involves filtering the raw measured EM signal through a differentiator prior to further data analysis. Applying the proposed method to various exemplary datasets including very low frequency EEG recordings, epileptic seizure recordings, MEG data and Evoked Response data showed that this compensating procedure provides a flat spectral base onto which event related peaks can be clearly observed. Findings suggest that the proposed filter is a useful tool for the analysis of physiological data especially in revealing very low frequency peaks which may otherwise be obscured by the 1/f spectral activity inherent in EEG/MEG recordings.

Comparison of Portable and Bench-Top Spectrometers for Mid-Infrared Diffuse Reflectance Measurements of Soils.

PubMed

Hutengs, Christopher; Ludwig, Bernard; Jung, András; Eisele, Andreas; Vohland, Michael

2018-03-27

Mid-infrared (MIR) spectroscopy has received widespread interest as a method to complement traditional soil analysis. Recently available portable MIR spectrometers additionally offer potential for on-site applications, given sufficient spectral data quality. We therefore tested the performance of the Agilent 4300 Handheld FTIR (DRIFT spectra) in comparison to a Bruker Tensor 27 bench-top instrument in terms of (i) spectral quality and measurement noise quantified by wavelet analysis; (ii) accuracy of partial least squares (PLS) calibrations for soil organic carbon (SOC), total nitrogen (N), pH, clay and sand content with a repeated cross-validation analysis; and (iii) key spectral regions for these soil properties identified with a Monte Carlo spectral variable selection approach. Measurements and multivariate calibrations with the handheld device were as good as or slightly better than Bruker equipped with a DRIFT accessory, but not as accurate as with directional hemispherical reflectance (DHR) data collected with an integrating sphere. Variations in noise did not markedly affect the accuracy of multivariate PLS calibrations. Identified key spectral regions for PLS calibrations provided a good match between Agilent and Bruker DHR data, especially for SOC and N. Our findings suggest that portable FTIR instruments are a viable alternative for MIR measurements in the laboratory and offer great potential for on-site applications.

A comparison of spectral mixture analysis an NDVI for ascertaining ecological variables

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Bateson, C. Ann; Curtiss, Brian; Benning, Tracy L.

1993-01-01

In this study, we compare the performance of spectral mixture analysis to the Normalized Difference Vegetation Index (NDVI) in detecting change in a grassland across topographically-induced nutrient gradients and different management schemes. The Konza Prairie Research Natural Area, Kansas, is a relatively homogeneous tallgrass prairie in which change in vegetation productivity occurs with respect to topographic positions in each watershed. The area is the site of long-term studies of the influence of fire and grazing on tallgrass production and was the site of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) from 1987 to 1989. Vegetation indices such as NDVI are commonly used with imagery collected in few (less than 10) spectral bands. However, the use of only two bands (e.g. NDVI) does not adequately account for the complex of signals making up most surface reflectance. Influences from background spectral variation and spatial heterogeneity may confound the direct relationship with biological or biophysical variables. High dimensional multispectral data allows for the application position of techniques such as derivative analysis and spectral curve fitting, thereby increasing the probability of successfully modeling the reflectance from mixed surfaces. The higher number of bands permits unmixing of a greater number of surface components, separating the vegetation signal for further analyses relevant to biological variables.

The continuum spectral characteristics of gamma ray bursts observed by BATSE

NASA Technical Reports Server (NTRS)

Pendleton, Geoffrey N.; Paciesas, William S.; Briggs, Michael S.; Mallozzi, Robert S.; Koshut, Tom M.; Fishman, Gerald J.; Meegan, Charles A.; Wilson, Robert B.; Harmon, Alan B.; Kouveliotou, Chryssa

1994-01-01

Distributions of the continuum spectral characteristics of 260 bursts in the first Burst and Transient Source Experiment (BATSE) catalog are presented. The data are derived from flux ratios calculated from the BATSE Large Area Detector (LAD) four channel discriminator data. The data are converted from counts to photons using a direct spectral inversion technique to remove the effects of atmospheric scattering and the energy dependence of the detector angular response. Although there are intriguing clusterings of bursts in the spectral hardness ratio distributions, no evidence for the presence of distinct burst classes based on spectral hardness ratios alone is found. All subsets of bursts selected for their spectral characteristics in this analysis exhibit spatial distributions consistent with isotropy. The spectral diversity of the burst population appears to be caused largely by the highly variable nature of the burst production mechanisms themselves.

Analysis on the optical aberration effect on spectral resolution of coded aperture spectroscopy

NASA Astrophysics Data System (ADS)

Hao, Peng; Chi, Mingbo; Wu, Yihui

2017-10-01

The coded aperture spectrometer can achieve high throughput and high spectral resolution by replacing the traditional single slit with two-dimensional array slits manufactured by MEMS technology. However, the sampling accuracy of coding spectrum image will be distorted due to the existence of system aberrations, machining error, fixing errors and so on, resulting in the declined spectral resolution. The influence factor of the spectral resolution come from the decode error, the spectral resolution of each column, and the column spectrum offset correction. For the Czerny-Turner spectrometer, the spectral resolution of each column most depend on the astigmatism, in this coded aperture spectroscopy, the uncorrected astigmatism does result in degraded performance. Some methods must be used to reduce or remove the limiting astigmatism. The curvature of field and the spectral curvature can be result in the spectrum revision errors.

Assessing mine drainage pH from the color and spectral reflectance of chemical precipitates

USGS Publications Warehouse

Williams, D.J.; Bigham, J.M.; Cravotta, C.A.; Traina, S.J.; Anderson, J.E.; Lyon, J.G.

2002-01-01

The pH of mine impacted waters was estimated from the spectral reflectance of resident sediments composed mostly of chemical precipitates. Mine drainage sediments were collected from sites in the Anthracite Region of eastern Pennsylvania, representing acid to near neutral pH. Sediments occurring in acidic waters contained primarily schwertmannite and goethite while near neutral waters produced ferrihydrite. The minerals comprising the sediments occurring at each pH mode were spectrally separable. Spectral angle difference mapping was used to correlate sediment color with stream water pH (r2=0.76). Band-center and band-depth analysis of spectral absorption features were also used to discriminate ferrihydrite and goethite and/or schwertmannite by analyzing the 4T1??? 6A1 crystal field transition (900-1000 nm). The presence of these minerals accurately predicted stream water pH (r2=0.87) and provided a qualitative estimate of dissolved SO4 concentrations. Spectral analysis results were used to analyze airborne digital multispectral video (DMSV) imagery for several sites in the region. The high spatial resolution of the DMSV sensor allowed for precise mapping of the mine drainage sediments. The results from this study indicate that airborne and space-borne imaging spectrometers may be used to accurately classify streams impacted by acid vs. neutral-to-alkaline mine drainage after appropriate spectral libraries are developed.

Reconstructing spectral cues for sound localization from responses to rippled noise stimuli.

PubMed

Van Opstal, A John; Vliegen, Joyce; Van Esch, Thamar

2017-01-01

Human sound localization in the mid-saggital plane (elevation) relies on an analysis of the idiosyncratic spectral shape cues provided by the head and pinnae. However, because the actual free-field stimulus spectrum is a-priori unknown to the auditory system, the problem of extracting the elevation angle from the sensory spectrum is ill-posed. Here we test different spectral localization models by eliciting head movements toward broad-band noise stimuli with randomly shaped, rippled amplitude spectra emanating from a speaker at a fixed location, while varying the ripple bandwidth between 1.5 and 5.0 cycles/octave. Six listeners participated in the experiments. From the distributions of localization responses toward the individual stimuli, we estimated the listeners' spectral-shape cues underlying their elevation percepts, by applying maximum-likelihood estimation. The reconstructed spectral cues resulted to be invariant to the considerable variation in ripple bandwidth, and for each listener they had a remarkable resemblance to the idiosyncratic head-related transfer functions (HRTFs). These results are not in line with models that rely on the detection of a single peak or notch in the amplitude spectrum, nor with a local analysis of first- and second-order spectral derivatives. Instead, our data support a model in which the auditory system performs a cross-correlation between the sensory input at the eardrum-auditory nerve, and stored representations of HRTF spectral shapes, to extract the perceived elevation angle.

Univariate and multivariate molecular spectral analyses of lipid related molecular structural components in relation to nutrient profile in feed and food mixtures

NASA Astrophysics Data System (ADS)

Abeysekara, Saman; Damiran, Daalkhaijav; Yu, Peiqiang

2013-02-01

The objectives of this study were (i) to determine lipid related molecular structures components (functional groups) in feed combination of cereal grain (barley, Hordeum vulgare) and wheat (Triticum aestivum) based dried distillers grain solubles (wheat DDGSs) from bioethanol processing at five different combination ratios using univariate and multivariate molecular spectral analyses with infrared Fourier transform molecular spectroscopy, and (ii) to correlate lipid-related molecular-functional structure spectral profile to nutrient profiles. The spectral intensity of (i) CH3 asymmetric, CH2 asymmetric, CH3 symmetric and CH2 symmetric groups, (ii) unsaturation (Cdbnd C) group, and (iii) carbonyl ester (Cdbnd O) group were determined. Spectral differences of functional groups were detected by hierarchical cluster analysis (HCA) and principal components analysis (PCA). The results showed that the combination treatments significantly inflicted modifications (P < 0.05) in nutrient profile and lipid related molecular spectral intensity (CH2 asymmetric stretching peak height, CH2 symmetric stretching peak height, ratio of CH2 to CH3 symmetric stretching peak intensity, and carbonyl peak area). Ratio of CH2 to CH3 symmetric stretching peak intensity, and carbonyl peak significantly correlated with nutrient profiles. Both PCA and HCA differentiated lipid-related spectrum. In conclusion, the changes of lipid molecular structure spectral profiles through feed combination could be detected using molecular spectroscopy. These changes were associated with nutrient profiles and functionality.

Multichannel spectral mode of the ALOHA up-conversion interferometer

NASA Astrophysics Data System (ADS)

Lehmann, L.; Darré, P.; Boulogne, H.; Delage, L.; Grossard, L.; Reynaud, F.

2018-06-01

In this paper, we propose a multichannel spectral configuration of the Astronomical Light Optical Hybrid Analysis (ALOHA) instrument dedicated to high-resolution imaging. A frequency conversion process is implemented in each arm of an interferometer to transfer the astronomical light to a shorter wavelength domain. Exploiting the spectral selectivity of this non-linear optical process, we propose to use a set of independent pump lasers in order to simultaneously study multiple spectral channels. This principle is experimentally demonstrated with a dual-channel configuration as a proof-of-principle.

SDP_mharwit_1: Demonstration of HIFI Linear Polarization Analysis of Spectral Features

NASA Astrophysics Data System (ADS)

Harwit, M.

2010-03-01

We propose to observe the polarization of the 621 GHz water vapor maser in VY Canis Majoris to demonstrate the capability of HIFI to make polarization observations of Far-Infrared/Submillimeter spectral lines. The proposed Demonstration Phase would: - Show that HIFI is capable of interesting linear polarization measurements of spectral lines; - Test out the highest spectral resolving power to sort out closely spaced Doppler components; - Determine whether the relative intensities predicted by Neufeld and Melnick are correct; - Record the degree and direction of linear polarization for the closely-Doppler shifted peaks.

A far-infrared spatial/spectral Fourier interferometry laboratory-based testbed instrument

NASA Astrophysics Data System (ADS)

Spencer, Locke D.; Naylor, David A.; Scott, Jeremy P.; Weiler, Vince F.; MacCrimmon, Roderick K.; Sitwell, Geoffrey R. H.; Ade, Peter A. R.

2016-07-01

We describe the current status, including preliminary design, characterization efforts, and recent progress, in the development of a spatial/spectral double Fourier laboratory-based interferometer testbed instrument within the Astronomical Instrumentation Group (AIG) laboratories at the University of Lethbridge, Canada (UL). Supported by CRC, CFI, and NSERC grants, this instrument development will provide laboratory demonstration of spatial-spectral interferometry with a concentration of furthering progress in areas including the development of spatial/spectral interferometry observation, data processing, characterization, and analysis techniques in the Far-Infrared (FIR) region of the electromagnetic spectrum.

A multispectral analysis of algal bloom in the Gulf of Mexico

NASA Technical Reports Server (NTRS)

Johnson, W. R.; Norris, D. R.

1977-01-01

Skylab multispectral scanner data acquired on January 21, 1974, were used to study the spectral characteristics of an algal bloom in the Gulf of Mexico west of Fort Myers, Florida. Radiance profiles of the water and algae were prepared with data from ten bands of the S192 scanner covering the spectral range from .42 to 2.35 micrometers. The high spectral response in the near-infrared spectral bands implies a possible classification and discrimination parameter for detection of blooms of phytoplankton concentrations such as the so-called red tides of Florida.

Effect of non-Poisson samples on turbulence spectra from laser velocimetry

NASA Technical Reports Server (NTRS)

Sree, Dave; Kjelgaard, Scott O.; Sellers, William L., III

1994-01-01

Spectral analysis of laser velocimetry (LV) data plays an important role in characterizing a turbulent flow and in estimating the associated turbulence scales, which can be helpful in validating theoretical and numerical turbulence models. The determination of turbulence scales is critically dependent on the accuracy of the spectral estimates. Spectral estimations from 'individual realization' laser velocimetry data are typically based on the assumption of a Poisson sampling process. What this Note has demonstrated is that the sampling distribution must be considered before spectral estimates are used to infer turbulence scales.

The spectral applications of Beer-Lambert law for some biological and dosimetric materials

NASA Astrophysics Data System (ADS)

Içelli, Orhan; Yalçin, Zeynel; Karakaya, Vatan; Ilgaz, Işıl P.

2014-08-01

The aim of this study is to conduct quantitative and qualitative analysis of biological and dosimetric materials which contain organic and inorganic materials and to make the determination by using the spectral theorem Beer-Lambert law. Beer-Lambert law is a system of linear equations for the spectral theory. It is possible to solve linear equations with a non-zero coefficient matrix determinant forming linear equations. Characteristic matrix of the linear equation with zero determinant is called point spectrum at the spectral theory.

Optical and photoconductivity spectra of novel Ag₂In₂SiS₆ and Ag₂In₂GeS₆ chalcogenide crystals.

PubMed

Chmiel, M; Piasecki, M; Myronchuk, G; Lakshminarayana, G; Reshak, Ali H; Parasyuk, O G; Kogut, Yu; Kityk, I V

2012-06-01

Complex spectral studies of near-band gap and photoconductive spectra for novel Ag(2)In(2)SiS(6) and Ag(2)In(2)GeS(6) single crystals are presented. The spectral dependences of photoconductivity clearly show an existence of spectral maxima within the 450 nm-540 nm and 780 nm-920 nm. The fundamental absorption edge is analyzed by Urbach rule. The origin of the spectral photoconductivity spectral maxima is discussed. Temperature dependences of the spectra were done. The obtained spectral features allow to propose the titled crystals as photosensors. An analysis of the absorption and photoconductivity spectra is given within a framework of oversimplified spectroscopic model of complex chalcogenide crystals. Copyright © 2012 Elsevier B.V. All rights reserved.

Slitless Solar Spectroscopy

NASA Technical Reports Server (NTRS)

Davila, Joseph M.; Jones, Sahela

2011-01-01

Spectrographs have traditionally suffered from the inability to obtain line intensities, widths, and Doppler shifts over large spatial regions of the Sun quickly because of the narrow instantaneous field of view. This has limited the spectroscopic analysis of rapidly varying solar features like, flares, CME eruptions, coronal jets, and reconnection regions. Imagers have provided high time resolution images of the full Sun with limited spectral resolution. In this paper we present recent advances in deconvolving spectrally dispersed images obtained through broad slits. We use this new theoretical formulation to examine the effectiveness of various potential observing scenarios, spatial and spectral resolutions, signal to noise ratio, and other instrument characteristics. This information will lay the foundation for a new generation of spectral imagers optimized for slitless spectral operation, while retaining the ability to obtain spectral information in transient solar events.

Multispectral Image Compression for Improvement of Colorimetric and Spectral Reproducibility by Nonlinear Spectral Transform

NASA Astrophysics Data System (ADS)

Yu, Shanshan; Murakami, Yuri; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki

2006-09-01

The article proposes a multispectral image compression scheme using nonlinear spectral transform for better colorimetric and spectral reproducibility. In the method, we show the reduction of colorimetric error under a defined viewing illuminant and also that spectral accuracy can be improved simultaneously using a nonlinear spectral transform called Labplus, which takes into account the nonlinearity of human color vision. Moreover, we show that the addition of diagonal matrices to Labplus can further preserve the spectral accuracy and has a generalized effect of improving the colorimetric accuracy under other viewing illuminants than the defined one. Finally, we discuss the usage of the first-order Markov model to form the analysis vectors for the higher order channels in Labplus to reduce the computational complexity. We implement a multispectral image compression system that integrates Labplus with JPEG2000 for high colorimetric and spectral reproducibility. Experimental results for a 16-band multispectral image show the effectiveness of the proposed scheme.

Spectral Clustering and Geomorphological Analysis on Mercury Hollows

NASA Astrophysics Data System (ADS)

Lucchetti, A.; Pajola, M.; Galluzzi, V.; Giacomini, L.; Carli, C.; Cremonese, G.; Marzo, G. A.; Massironi, M.; Roush, T.

2018-05-01

Characterization of hollows located in different craters to understand whether there is a similar trend from a compositional point of view, and whether a possible correlation exists between spectral behavior of hollows and geomorphological units.

Colour mapping of the Shakespeare (H-03) quadrangle of Mercury

NASA Astrophysics Data System (ADS)

Bott, N.; Doressoundiram, A.; Perna, D.; Zambon, F.; Carli, C.; Capaccioni, F.

2017-09-01

We will present a colour mapping of the Shakespeare (H-03) quadrangle of Mercury, as well as the spectral analysis and a preliminary correlation between the spectral properties and the geological units.

Solar and Climate Variation Relationships Analyzed from Chile Tree Ring Width Time Series (1587 - 1994 A.D.)

NASA Astrophysics Data System (ADS)

Rigozo, Nr; Nordemann, Djr; Faria, Hh; Echer, E.; Vieira, Lea; Prestes, A.

This work presents a study of the relations between solar and climate variations during the last four centuries by spectral analysis of tree ring index and sunspot number time series. Trees used for this study were Pilgerodendron cupressoides from Glaciar Pio XI, in Chile. The spectral analysis of tree ring index shows that 11, 22 and 80 year periodicities of the solar cycle were present in this tree ring data with 0.95 confidence level. This result suggests a solar modulation of climate variations, as recorded by the tree ring growth. Short-term variations, between 2 - 7 years, are also present in tree ring data. Therefore spectral analysis clearly shows that both, solar and climate factors, are recorded in the tree ring data.

Practical Approach for Hyperspectral Image Processing in Python

NASA Astrophysics Data System (ADS)

Annala, L.; Eskelinen, M. A.; Hämäläinen, J.; Riihinen, A.; Pölönen, I.

2018-04-01

Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

Measurement analysis of two radials with a common-origin point and its application.

PubMed

Liu, Zhenyao; Yang, Jidong; Zhu, Weiwei; Zhou, Shang; Tan, Xuanping

2017-08-01

In spectral analysis, a chemical component is usually identified by its characteristic spectra, especially the peaks. If two components have overlapping spectral peaks, they are generally considered to be indiscriminate in current analytical chemistry textbooks and related literature. However, if the intensities of the overlapping major spectral peaks are additive, and have different rates of change with respect to variations in the concentration of the individual components, a simple method, named the 'common-origin ray', for the simultaneous determination of two components can be established. Several case studies highlighting its applications are presented. Copyright © 2017 John Wiley & Sons, Ltd.

A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis.

PubMed

Hsieh, Sheng-Hsun; Li, Yung-Hui; Wang, Wei; Tien, Chung-Hao

2018-03-06

In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL) pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR) was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme.

Ab initio calculations for the spectral analysis of dimethyl ether (CH_3OCH_3) and their isotopologues

NASA Astrophysics Data System (ADS)

Senent, M. L.; Villa, M.; Dominguez-Gomez, R.; Alvarez-Bajo, O.; Carvajal, M.

2011-05-01

Dimethyl ether is a complex interstellar molecule with two internal rotors, which has a high abundance in the star-forming regions. This point, jointed with the recent development of the last-generation observatories operating at the sub-mm and mm wavelengths, has motivated a new laboratory spectral recording in this frequency range. In spite of that, the rotational spectra was only analysed in depth within its vibrational ground state and a new spectral analysis within the fundamental torsional states is in progress. These analysis were carried out with ERHAM, a global model that takes into account the large amplitude motions owing to the two equivalent internal CH3 tops. Nevertheless, their torsional modes in principle interact with the bending COC mode and an appropiate torsional-bending description would be needed in order to analyse the rotational spectra within higher excited states. In this work, a new analysis of the COC bending and the CH3 torsional degrees of freedom has been carried out by means of ab initio calculations. A new and more accurate three-dimensional Potential Energy Surface (PES), is obtained using the CCSD(T) level of theory. This approach has also been applied to other isotopologues of interest, as 13C-dimethyl ether and the monodeuterated species. The purpose of this study is to help in the assignment of new spectral lines of these species and hence to contribute in the spectral cleaning of the astronomical observations to the interstellar medium.

[Application of AOTF in spectral analysis. 3. Application of AOTF in atomic emission spectral analysis].

PubMed

Chen, Ze-yong; Peng, Rong-fei; Zhang, Zhan-xia

2002-06-01

An atomic emission spectrometer based on acousto-optic tunable filter (AOTF) was self-constructed and was used to evaluate its practical use in atomic emission analysis. The AOTF used was of model TEAF5-0.36-0.52-S (Brimrose, USA) and the frequency of the direct digital RF synthesizer ranges from 100 MHz to 200 MHz. ICP and PMT were used as light source and detector respectively. The software, written in Visual C++ and running on the Windows 98 platform, is of an utility program system having two data banks and multiwindows. The wavelength calibration was performed with 14 emission lines of Ca, Y, Li, Eu, Sr and Ba using a tenth-order polynomial for line fitting method. The absolute error of the peak position was less than 0.1 nm, and the peak deviation was only 0.04 nm as the PMT varied from 337.5 V to 412.5 V. The scanning emission spectra and the calibration curves of Ba, Y, Eu, Sc and Sr are presented. Their average correlation coefficient was 0.9991 and their detection limits were in the range of 0.051 to 0.97 micrograms.mL-1 respectively. The detection limit can be improved under optimized operating conditions. However, the spectral resolution is only 2.1 nm at the wavelength of 488 nm. Evidently, this poor spectral resolution would restrict the application of AOTF in atomic emission spectral analysis, unless an enhancing techniques is integrated in it.

Spectral Dynamics of Resting State fMRI Within the Ventral Tegmental Area and Dorsal Raphe Nuclei in Medication-Free Major Depressive Disorder in Young Adults.

PubMed

Wohlschläger, Afra; Karne, Harish; Jordan, Denis; Lowe, Mark J; Jones, Stephen E; Anand, Amit

2018-01-01

Background: Dorsal raphe nucleus (DRN) and ventral tegmental area (VTA) are major brainstem monamine nuclei consisting of serotonin and dopamine neurons respectively. Animal studies show that firing patterns in both nuclei are altered when animals exhibit depression like behaviors. Functional MRI studies in humans have shown reduced VTA activation and DRN connectivity in depression. This study for the first time aims at investigating the functional integrity of local neuronal firing concurrently in both the VTA and DRN in vivo in humans using spectral analysis of resting state low frequency fluctuation fMRI. Method: A total of 97 medication-free subjects-67 medication-free young patients (ages 18-30) with major depressive disorder and 30 closely matched healthy controls were included in the study to detect aberrant dynamics in DRN and VTA. For the investigation of altered localized dynamics we conducted power spectral analysis and above this spectral cross correlation between the two groups. Complementary to this, spectral dependence of permutation entropy, an information theoretical measure, was compared between groups. Results: Patients displayed significant spectral slowing in VTA vs. controls ( p = 0.035, corrected). In DRN, spectral slowing was less pronounced, but the amount of slowing significantly correlated with 17-item Hamilton Depression Rating scores of depression severity ( p = 0.038). Signal complexity as assessed via permutation entropy showed spectral alterations inline with the results on spectral slowing. Conclusion: Our results indicate that altered functional dynamics of VTA and DRN in depression can be detected from regional fMRI signal. On this basis, impact of antidepressant treatment and treatment response can be assessed using these markers in future studies.

A New View of Earthquake Ground Motion Data: The Hilbert Spectral Analysis

NASA Technical Reports Server (NTRS)

Huang, Norden; Busalacchi, Antonio J. (Technical Monitor)

2000-01-01

A brief description of the newly developed Empirical Mode Decomposition (ENID) and Hilbert Spectral Analysis (HSA) method will be given. The decomposition is adaptive and can be applied to both nonlinear and nonstationary data. Example of the method applied to a sample earthquake record will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

Design framework for a spectral mask for a plenoptic camera

NASA Astrophysics Data System (ADS)

Berkner, Kathrin; Shroff, Sapna A.

2012-01-01

Plenoptic cameras are designed to capture different combinations of light rays from a scene, sampling its lightfield. Such camera designs capturing directional ray information enable applications such as digital refocusing, rotation, or depth estimation. Only few address capturing spectral information of the scene. It has been demonstrated that by modifying a plenoptic camera with a filter array containing different spectral filters inserted in the pupil plane of the main lens, sampling of the spectral dimension of the plenoptic function is performed. As a result, the plenoptic camera is turned into a single-snapshot multispectral imaging system that trades-off spatial with spectral information captured with a single sensor. Little work has been performed so far on analyzing diffraction effects and aberrations of the optical system on the performance of the spectral imager. In this paper we demonstrate simulation of a spectrally-coded plenoptic camera optical system via wave propagation analysis, evaluate quality of the spectral measurements captured at the detector plane, and demonstrate opportunities for optimization of the spectral mask for a few sample applications.

The SpeX Prism Library Analysis Toolkit: Design Considerations and First Results

NASA Astrophysics Data System (ADS)

Burgasser, Adam J.; Aganze, Christian; Escala, Ivana; Lopez, Mike; Choban, Caleb; Jin, Yuhui; Iyer, Aishwarya; Tallis, Melisa; Suarez, Adrian; Sahi, Maitrayee

2016-01-01

Various observational and theoretical spectral libraries now exist for galaxies, stars, planets and other objects, which have proven useful for classification, interpretation, simulation and model development. Effective use of these libraries relies on analysis tools, which are often left to users to develop. In this poster, we describe a program to develop a combined spectral data repository and Python-based analysis toolkit for low-resolution spectra of very low mass dwarfs (late M, L and T dwarfs), which enables visualization, spectral index analysis, classification, atmosphere model comparison, and binary modeling for nearly 2000 library spectra and user-submitted data. The SpeX Prism Library Analysis Toolkit (SPLAT) is being constructed as a collaborative, student-centered, learning-through-research model with high school, undergraduate and graduate students and regional science teachers, who populate the database and build the analysis tools through quarterly challenge exercises and summer research projects. In this poster, I describe the design considerations of the toolkit, its current status and development plan, and report the first published results led by undergraduate students. The combined data and analysis tools are ideal for characterizing cool stellar and exoplanetary atmospheres (including direct exoplanetary spectra observations by Gemini/GPI, VLT/SPHERE, and JWST), and the toolkit design can be readily adapted for other spectral datasets as well.This material is based upon work supported by the National Aeronautics and Space Administration under Grant No. NNX15AI75G. SPLAT code can be found at https://github.com/aburgasser/splat.

Quantitative methods and detection techniques in hyperspectral imaging involving medical and other applications

NASA Astrophysics Data System (ADS)

Roy, Ankita

2007-12-01

This research using Hyperspectral imaging involves recognizing targets through spatial and spectral matching and spectral un-mixing of data ranging from remote sensing to medical imaging kernels for clinical studies based on Hyperspectral data-sets generated using the VFTHSI [Visible Fourier Transform Hyperspectral Imager], whose high resolution Si detector makes the analysis achievable. The research may be broadly classified into (I) A Physically Motivated Correlation Formalism (PMCF), which places both spatial and spectral data on an equivalent mathematical footing in the context of a specific Kernel and (II) An application in RF plasma specie detection during carbon nanotube growing process. (III) Hyperspectral analysis for assessing density and distribution of retinopathies like age related macular degeneration (ARMD) and error estimation enabling the early recognition of ARMD, which is treated as an ill-conditioned inverse imaging problem. The broad statistical scopes of this research are two fold-target recognition problems and spectral unmixing problems. All processes involve experimental and computational analysis of Hyperspectral data sets is presented, which is based on the principle of a Sagnac Interferometer, calibrated to obtain high SNR levels. PMCF computes spectral/spatial/cross moments and answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required precisely for a particular target recognition. Spectral analysis of RF plasma radicals, typically Methane plasma and Argon plasma using VFTHSI has enabled better process monitoring during growth of vertically aligned multi-walled carbon nanotubes by instant registration of the chemical composition or density changes temporally, which is key since a significant correlation can be found between plasma state and structural properties. A vital focus of this dissertation is towards medical Hyperspectral imaging applied to retinopathies like age related macular degeneration targets taken with a Fundus imager, which is akin to the VFTHSI. Detection of the constituent components in the diseased hyper-pigmentation area is also computed. The target or reflectance matrix is treated as a highly ill-conditioned spectral un-mixing problem, to which methodologies like inverse techniques, principal component analysis (PCA) and receiver operating curves (ROC) for precise spectral recognition of infected area. The region containing ARMD was easily distinguishable from the spectral mesh plots over the entire band-pass area. Once the location was detected the PMCF coefficients were calculated by cross correlating a target of normal oxygenated retina with the deoxygenated one. The ROCs generated using PMCF shows 30% higher detection probability with improved accuracy than ROCs based on Spectral Angle Mapper (SAM). By spectral unmixing methods, the important endmembers/carotenoids of the MD pigment were found to be Xanthophyl and lutein, while beta-carotene which showed a negative correlation in the unconstrained inverse problem is a supplement given to ARMD patients to prevent the disease and does not occur in the eye. Literature also shows degeneration of meso-zeaxanthin. Ophthalmologists may assert the presence of ARMD and commence the diagnosis process if the Xanthophyl pigment have degenerated 89.9%, while the lutein has decayed almost 80%, as found deduced computationally. This piece of current research takes it to the next level of precise investigation in the continuing process of improved clinical findings by correlating the microanatomy of the diseased fovea and shows promise of an early detection of this disease.

Spectral characteristics of plasma sheet ion and electron populations during undisturbed geomagnetic conditions

NASA Technical Reports Server (NTRS)

Christon, S. P.; Williams, D. J.; Mitchell, D. G.; Frank, L. A.; Huang, C. Y.

1989-01-01

The spectral characteristics of plasma-sheet ion and electron populations during periods of low geomagnetic activity were determined from the analysis of 127 one-hour average samples of central plasma sheet ions and electrons. Particle data from the ISEE-1 low-energy proton and electron differential energy analyzer and medium-energy particle instrument were combined to obtain differential energy spectra in the plasma sheet at geocentric radial distances above 12 earth radii. The relationships between the ion and electron spectral shapes and between the spectral shapes and the geomagnetic activity index were statistically investigated. It was found that the presence of interplanetary particle fluxes does not affect the plasma sheet particle spectral shape.

Development and Evaluation of a Spectral Analysis Method to Eliminate Organic Interference with Cavity Ring-Down Measurements of Water Isotope Ratios.

NASA Astrophysics Data System (ADS)

Lin, Z.; Kim-Hak, D.; Popp, B. N.; Wallsgrove, N.; Kagawa-Viviani, A.; Johnson, J.

2017-12-01

Cavity ring-down spectroscopy (CRDS) is a technology based on the spectral absorption of gas molecules of interest at specific spectral regions. The CRDS technique enables the analysis of hydrogen and oxygen stable isotope ratios of water by directly measuring individual isotopologue absorption peaks such as H16OH, H18OH, and D16OH. Early work demonstrated that the accuracy of isotope analysis by CRDS and other laser-based absorption techniques could be compromised by spectral interference from organic compounds, in particular methanol and ethanol, which can be prevalent in ecologically-derived waters. There have been several methods developed by various research groups including Picarro to address the organic interference challenge. Here, we describe an organic fitter and a post-processing algorithm designed to improve the accuracy of the isotopic analysis of the "organic contaminated" water specifically for Picarro models L2130-i and L2140-i. To create the organic fitter, the absorption features of methanol around 7200 cm-1 were characterized and incorporated into spectral analysis. Since there was residual interference remaining after applying the organic fitter, a statistical model was also developed for post-processing correction. To evaluate the performance of the organic fitter and the postprocessing correction, we conducted controlled experiments on the L2130-i for two water samples with different isotope ratios blended with varying amounts of methanol (0-0.5%) and ethanol (0-5%). When the original fitter was not used for spectral analysis, the addition of 0.5% methanol changed the apparent isotopic composition of the water samples by +62‰ for δ18O values and +97‰ for δ2H values, and the addition of 5% ethanol changed the apparent isotopic composition by -0.5‰ for δ18O values and -3‰ for δ2H values. When the organic fitter was used for spectral analysis, the maximum methanol-induced errors were reduced to +4‰ for δ18O values and +5‰ for δ2H values, and the maximum ethanol-induced errors were unchanged. When the organic fitter was combined with the post-processing correction, up to 99.8% of the total methanol-induced errors and 96% of the total ethanol-induced errors could be corrected. The applicability of the algorithm to natural samples such as plant and soil waters will be investigated.

Multicomponent quantitative spectroscopic analysis without reference substances based on ICA modelling.

PubMed

Monakhova, Yulia B; Mushtakova, Svetlana P

2017-05-01

A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.

Flow Cytometry Data Preparation Guidelines for Improved Automated Phenotypic Analysis.

PubMed

Jimenez-Carretero, Daniel; Ligos, José M; Martínez-López, María; Sancho, David; Montoya, María C

2018-05-15

Advances in flow cytometry (FCM) increasingly demand adoption of computational analysis tools to tackle the ever-growing data dimensionality. In this study, we tested different data input modes to evaluate how cytometry acquisition configuration and data compensation procedures affect the performance of unsupervised phenotyping tools. An analysis workflow was set up and tested for the detection of changes in reference bead subsets and in a rare subpopulation of murine lymph node CD103 + dendritic cells acquired by conventional or spectral cytometry. Raw spectral data or pseudospectral data acquired with the full set of available detectors by conventional cytometry consistently outperformed datasets acquired and compensated according to FCM standards. Our results thus challenge the paradigm of one-fluorochrome/one-parameter acquisition in FCM for unsupervised cluster-based analysis. Instead, we propose to configure instrument acquisition to use all available fluorescence detectors and to avoid integration and compensation procedures, thereby using raw spectral or pseudospectral data for improved automated phenotypic analysis. Copyright © 2018 by The American Association of Immunologists, Inc.

Linearized spectrum correlation analysis for line emission measurements

NASA Astrophysics Data System (ADS)

Nishizawa, T.; Nornberg, M. D.; Den Hartog, D. J.; Sarff, J. S.

2017-08-01

A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100-200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.

An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

NASA Astrophysics Data System (ADS)

Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

2017-09-01

Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

Feature Transformation Detection Method with Best Spectral Band Selection Process for Hyper-spectral Imaging

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike; Brickhouse, Mark

2015-11-01

We present a newly developed feature transformation (FT) detection method for hyper-spectral imagery (HSI) sensors. In essence, the FT method, by transforming the original features (spectral bands) to a different feature domain, may considerably increase the statistical separation between the target and background probability density functions, and thus may significantly improve the target detection and identification performance, as evidenced by the test results in this paper. We show that by differentiating the original spectral, one can completely separate targets from the background using a single spectral band, leading to perfect detection results. In addition, we have proposed an automated best spectral band selection process with a double-threshold scheme that can rank the available spectral bands from the best to the worst for target detection. Finally, we have also proposed an automated cross-spectrum fusion process to further improve the detection performance in lower spectral range (<1000 nm) by selecting the best spectral band pair with multivariate analysis. Promising detection performance has been achieved using a small background material signature library for concept-proving, and has then been further evaluated and verified using a real background HSI scene collected by a HYDICE sensor.

Arbitrary-order Hilbert Spectral Analysis and Intermittency in Solar Wind Density Fluctuations

NASA Astrophysics Data System (ADS)

Carbone, Francesco; Sorriso-Valvo, Luca; Alberti, Tommaso; Lepreti, Fabio; Chen, Christopher H. K.; Němeček, Zdenek; Šafránková, Jana

2018-05-01

The properties of inertial- and kinetic-range solar wind turbulence have been investigated with the arbitrary-order Hilbert spectral analysis method, applied to high-resolution density measurements. Due to the small sample size and to the presence of strong nonstationary behavior and large-scale structures, the classical analysis in terms of structure functions may prove to be unsuccessful in detecting the power-law behavior in the inertial range, and may underestimate the scaling exponents. However, the Hilbert spectral method provides an optimal estimation of the scaling exponents, which have been found to be close to those for velocity fluctuations in fully developed hydrodynamic turbulence. At smaller scales, below the proton gyroscale, the system loses its intermittent multiscaling properties and converges to a monofractal process. The resulting scaling exponents, obtained at small scales, are in good agreement with those of classical fractional Brownian motion, indicating a long-term memory in the process, and the absence of correlations around the spectral-break scale. These results provide important constraints on models of kinetic-range turbulence in the solar wind.

Assessment of Infrared Sounder Radiometric Noise from Analysis of Spectral Residuals

NASA Astrophysics Data System (ADS)

Dufour, E.; Klonecki, A.; Standfuss, C.; Tournier, B.; Serio, C.; Masiello, G.; Tjemkes, S.; Stuhlmann, R.

2016-08-01

For the preparation and performance monitoring of the future generation of hyperspectral InfraRed sounders dedicated to the precise vertical profiling of the atmospheric state, such as the Meteosat Third Generation hyperspectral InfraRed Sounder, a reliable assessment of the instrument radiometric error covariance matrix is needed.Ideally, an inflight estimation of the radiometrric noise is recommended as certain sources of noise can be driven by the spectral signature of the observed Earth/ atmosphere radiance. Also, unknown correlated noise sources, generally related to incomplete knowledge of the instrument state, can be present, so a caracterisation of the noise spectral correlation is also neeed.A methodology, relying on the analysis of post-retreival spectral residuals, is designed and implemented to derive in-flight the covariance matrix on the basis of Earth scenes measurements. This methodology is successfully demonstrated using IASI observations as MTG-IRS proxy data and made it possible to highlight anticipated correlation structures explained by apodization and micro-vibration effects (ghost). This analysis is corroborated by a parallel estimation based on an IASI black body measurement dataset and the results of an independent micro-vibration model.

Hyperspectral Image Denoising Using a Nonlocal Spectral Spatial Principal Component Analysis

NASA Astrophysics Data System (ADS)

Li, D.; Xu, L.; Peng, J.; Ma, J.

2018-04-01

Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classification and so on. In this paper, we develop a noise reduction method based on principal component analysis (PCA) for hyperspectral imagery, which is dependent on the assumption that the noise can be removed by selecting the leading principal components. The main contribution of paper is to introduce the spectral spatial structure and nonlocal similarity of the HSIs into the PCA denoising model. PCA with spectral spatial structure can exploit spectral correlation and spatial correlation of HSI by using 3D blocks instead of 2D patches. Nonlocal similarity means the similarity between the referenced pixel and other pixels in nonlocal area, where Mahalanobis distance algorithm is used to estimate the spatial spectral similarity by calculating the distance in 3D blocks. The proposed method is tested on both simulated and real hyperspectral images, the results demonstrate that the proposed method is superior to several other popular methods in HSI denoising.

Spectral Study of Measles Epidemics: The Dependence of Spectral Gradient on the Population Size of the Community

NASA Astrophysics Data System (ADS)

Sumi, Ayako; Olsen, Lars Folke; Ohtomo, Norio; Tanaka, Yukio; Sawamura, Sadashi

2003-02-01

We have carried out spectral analysis of measles notifications in several communities in Denmark, UK and USA. The results confirm that each power spectral density (PSD) shows exponential characteristics, which are universally observed in the PSD for time series generated from nonlinear dynamical system. The exponential gradient increases with the population size. For almost all communities, many spectral lines observed in each PSD can be fully assigned to linear combinations of several fundamental periods, suggesting that the measles data are substantially noise-free. The optimum least squares fitting curve calculated using these fundamental periods essentially reproduces an underlying variation of the measles data, and an extension of the curve can be used to predict measles epidemics. For the communities with large population sizes, some PSD patterns obtained from segment time series analysis show a close resemblance to the PSD patterns at the initial stages of a period-doubling bifurcation process for the so-called susceptible/exposed/infectious/recovered (SEIR) model with seasonal forcing. The meaning of the relationship between the exponential gradient and the population size is discussed.

An evaluation of random analysis methods for the determination of panel damping

NASA Technical Reports Server (NTRS)

Bhat, W. V.; Wilby, J. F.

1972-01-01

An analysis is made of steady-state and non-steady-state methods for the measurement of panel damping. Particular emphasis is placed on the use of random process techniques in conjunction with digital data reduction methods. The steady-state methods considered use the response power spectral density, response autocorrelation, excitation-response crosspower spectral density, or single-sided Fourier transform (SSFT) of the response autocorrelation function. Non-steady-state methods are associated mainly with the use of rapid frequency sweep excitation. Problems associated with the practical application of each method are evaluated with specific reference to the case of a panel exposed to a turbulent airflow, and two methods, the power spectral density and the single-sided Fourier transform methods, are selected as being the most suitable. These two methods are demonstrated experimentally, and it is shown that the power spectral density method is satisfactory under most conditions, provided that appropriate corrections are applied to account for filter bandwidth and background noise errors. Thus, the response power spectral density method is recommended for the measurement of the damping of panels exposed to a moving airflow.

Karhunen-Loève treatment to remove noise and facilitate data analysis in sensing, spectroscopy and other applications.

PubMed

Zaharov, V V; Farahi, R H; Snyder, P J; Davison, B H; Passian, A

2014-11-21

Resolving weak spectral variations in the dynamic response of materials that are either dominated or excited by stochastic processes remains a challenge. Responses that are thermal in origin are particularly relevant examples due to the delocalized nature of heat. Despite its inherent properties in dealing with stochastic processes, the Karhunen-Loève expansion has not been fully exploited in measurement of systems that are driven solely by random forces or can exhibit large thermally driven random fluctuations. Here, we present experimental results and analysis of the archetypes (a) the resonant excitation and transient response of an atomic force microscope probe by the ambient random fluctuations and nanoscale photothermal sample response, and (b) the photothermally scattered photons in pump-probe spectroscopy. In each case, the dynamic process is represented as an infinite series with random coefficients to obtain pertinent frequency shifts and spectral peaks and demonstrate spectral enhancement for a set of compounds including the spectrally complex biomass. The considered cases find important applications in nanoscale material characterization, biosensing, and spectral identification of biological and chemical agents.

Decoding magnetoencephalographic rhythmic activity using spectrospatial information.

PubMed

Kauppi, Jukka-Pekka; Parkkonen, Lauri; Hari, Riitta; Hyvärinen, Aapo

2013-12-01

We propose a new data-driven decoding method called Spectral Linear Discriminant Analysis (Spectral LDA) for the analysis of magnetoencephalography (MEG). The method allows investigation of changes in rhythmic neural activity as a result of different stimuli and tasks. The introduced classification model only assumes that each "brain state" can be characterized as a combination of neural sources, each of which shows rhythmic activity at one or several frequency bands. Furthermore, the model allows the oscillation frequencies to be different for each such state. We present decoding results from 9 subjects in a four-category classification problem defined by an experiment involving randomly alternating epochs of auditory, visual and tactile stimuli interspersed with rest periods. The performance of Spectral LDA was very competitive compared with four alternative classifiers based on different assumptions concerning the organization of rhythmic brain activity. In addition, the spectral and spatial patterns extracted automatically on the basis of trained classifiers showed that Spectral LDA offers a novel and interesting way of analyzing spectrospatial oscillatory neural activity across the brain. All the presented classification methods and visualization tools are freely available as a Matlab toolbox. © 2013.

Analysis of bias voltage dependent spectral response in Ga0.51In0.49P/Ga0.99In0.01As/Ge triple junction solar cell

NASA Astrophysics Data System (ADS)

Sogabe, Tomah; Ogura, Akio; Okada, Yoshitaka

2014-02-01

Spectral response measurement plays great role in characterizing solar cell device because it directly reflects the efficiency by which the device converts the sunlight into an electrical current. Based on the spectral response results, the short circuit current of each subcell can be quantitatively determined. Although spectral response dependence on wavelength, i.e., the well-known external quantum efficiency (EQE), has been widely used in characterizing multijunction solar cell and has been well interpreted, detailed analysis of spectral response dependence on bias voltage (SR -Vbias) has not been reported so far. In this work, we have performed experimental and numerical studies on the SR -Vbias for Ga0.51In0.49P/Ga0.99In0.01As/Ge triple junction solar cell. Phenomenological description was given to clarify the mechanism of operation matching point variation in SR -Vbias measurements. The profile of SR-Vbias curve was explained in detail by solving the coupled two-diode current-voltage characteristic transcend formula for each subcell.

Corrigendum to "Enhancing endmember selection in multiple endmember spectral mixture analysis (MESMA) for urban impervious surface area mapping using spectral angle and spectral distance parameters" [Int. J. Appl. Earth Observ. Geoinf. 33 (2014) 290-301

NASA Astrophysics Data System (ADS)

Fan, Fenglei; Deng, Yingbin

2015-04-01

Since publication, the authors have been advised of one prior methodological article not cited in our original paper. The missed reference from the paper is "Andreou, C., Karathanassi, V., 2012. A novel multiple endmember spectral mixture analysis using spectral angle distance. Geoscience and Remote Sensing Symposium (IGARSS) 2012 IEEE International, 4110-4113." This reference "Andreou, C., Karathanassi, V., 2012 in proceeding of IGARSS" should be cited in the Part 3 and Table 1, whereby in the fist sentence of Part 3 and the last sentence of caption of Table 1. The following should be added (in Part 3: According to the traditional MESMA and referring to MESMA-SAD method which is reported by Andreou and Karathanassi; in caption of Table 1: Based on the MESMA-SAD method of Andreou and Karathanassi). We apologize to the authors and workers concerned for this oversight and are pleased to acknowledge their contributions.

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

Persistence of uranium emission in laser-produced plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

LaHaye, N. L.; Harilal, S. S., E-mail: hari@purdue.edu; Diwakar, P. K.

2014-04-28

Detection of uranium and other nuclear materials is of the utmost importance for nuclear safeguards and security. Optical emission spectroscopy of laser-ablated U plasmas has been presented as a stand-off, portable analytical method that can yield accurate qualitative and quantitative elemental analysis of a variety of samples. In this study, optimal laser ablation and ambient conditions are explored, as well as the spatio-temporal evolution of the plasma for spectral analysis of excited U species in a glass matrix. Various Ar pressures were explored to investigate the role that plasma collisional effects and confinement have on spectral line emission enhancement andmore » persistence. The plasma-ambient gas interaction was also investigated using spatially resolved spectra and optical time-of-flight measurements. The results indicate that ambient conditions play a very important role in spectral emission intensity as well as the persistence of excited neutral U emission lines, influencing the appropriate spectral acquisition conditions.« less

Sensitive Spectroscopic Analysis of Biomarkers in Exhaled Breath

NASA Astrophysics Data System (ADS)

Bicer, A.; Bounds, J.; Zhu, F.; Kolomenskii, A. A.; Kaya, N.; Aluauee, E.; Amani, M.; Schuessler, H. A.

2018-06-01

We have developed a novel optical setup which is based on a high finesse cavity and absorption laser spectroscopy in the near-IR spectral region. In pilot experiments, spectrally resolved absorption measurements of biomarkers in exhaled breath, such as methane and acetone, were carried out using cavity ring-down spectroscopy (CRDS). With a 172-cm-long cavity, an efficient optical path of 132 km was achieved. The CRDS technique is well suited for such measurements due to its high sensitivity and good spectral resolution. The detection limits for methane of 8 ppbv and acetone of 2.1 ppbv with spectral sampling of 0.005 cm-1 were achieved, which allowed to analyze multicomponent gas mixtures and to observe absorption peaks of 12CH4 and 13CH4. Further improvements of the technique have the potential to realize diagnostics of health conditions based on a multicomponent analysis of breath samples.

The Rhythm of Fairall 9. I. Observing the Spectral Variability With XMM-Newton and NuSTAR

NASA Technical Reports Server (NTRS)

Lohfink, A. M.; Reynolds, S. C.; Pinto, C.; Alston, W.; Boggs, S. E.; Christensen, F. E.; Craig, W. W.; Fabian, A.C; Hailey, C. J.; Harrison, F. A.;

Integrated fluorescence analysis system

DOEpatents

Buican, Tudor N.; Yoshida, Thomas M.

1992-01-01

An integrated fluorescence analysis system enables a component part of a sample to be virtually sorted within a sample volume after a spectrum of the component part has been identified from a fluorescence spectrum of the entire sample in a flow cytometer. Birefringent optics enables the entire spectrum to be resolved into a set of numbers representing the intensity of spectral components of the spectrum. One or more spectral components are selected to program a scanning laser microscope, preferably a confocal microscope, whereby the spectrum from individual pixels or voxels in the sample can be compared. Individual pixels or voxels containing the selected spectral components are identified and an image may be formed to show the morphology of the sample with respect to only those components having the selected spectral components. There is no need for any physical sorting of the sample components to obtain the morphological information.

Quantifying the effect of finite spectral bandwidth on extinction coefficient of species in laser absorption spectroscopy

NASA Astrophysics Data System (ADS)

Singh, Manjeet; Singh, Jaswant; Singh, Baljit; Ghanshyam, C.

2016-11-01

The aim of this study is to quantify the finite spectral bandwidth effect on laser absorption spectroscopy for a wide-band laser source. Experimental analysis reveals that the extinction coefficient of an analyte is affected by the bandwidth of the spectral source, which may result in the erroneous conclusions. An approximate mathematical model has been developed for optical intensities having Gaussian line shape, which includes the impact of source's spectral bandwidth in the equation for spectroscopic absorption. This is done by introducing a suitable first order and second order bandwidth approximation in the Beer-Lambert law equation for finite bandwidth case. The derived expressions were validated using spectroscopic analysis with higher SBW on a test sample, Rhodamine B. The concentrations calculated using proposed approximation, were in significant agreement with the true values when compared with those calculated with conventional approach.

Energy-Discriminative Performance of a Spectral Micro-CT System

PubMed Central

He, Peng; Yu, Hengyong; Bennett, James; Ronaldson, Paul; Zainon, Rafidah; Butler, Anthony; Butler, Phil; Wei, Biao; Wang, Ge

2013-01-01

Experiments were performed to evaluate the energy-discriminative performance of a spectral (multi-energy) micro-CT system. The system, designed by MARS (Medipix All Resolution System) Bio-Imaging Ltd. (Christchurch, New Zealand), employs a photon-counting energy-discriminative detector technology developed by CERN (European Organization for Nuclear Research). We used the K-edge attenuation characteristic of some known materials to calibrate the detector’s photon energy discrimination. For tomographic analysis, we used the compressed sensing (CS) based ordered-subset simultaneous algebraic reconstruction techniques (OS-SART) to reconstruct sample images, which is effective to reduce noise and suppress artifacts. Unlike conventional CT, the principal component analysis (PCA) method can be applied to extract and quantify additional attenuation information from a spectral CT dataset. Our results show that the spectral CT has a good energy-discriminative performance and provides more attenuation information than the conventional CT. PMID:24004864

Systems and methods for detection of blowout precursors in combustors

DOEpatents

Lieuwen, Tim C.; Nair, Suraj

2006-08-15

The present invention comprises systems and methods for detecting flame blowout precursors in combustors. The blowout precursor detection system comprises a combustor, a pressure measuring device, and blowout precursor detection unit. A combustion controller may also be used to control combustor parameters. The methods of the present invention comprise receiving pressure data measured by an acoustic pressure measuring device, performing one or a combination of spectral analysis, statistical analysis, and wavelet analysis on received pressure data, and determining the existence of a blowout precursor based on such analyses. The spectral analysis, statistical analysis, and wavelet analysis further comprise their respective sub-methods to determine the existence of blowout precursors.

NDVI and Panchromatic Image Correlation Using Texture Analysis

DTIC Science & Technology

2010-03-01

6 Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm (From Perry...should help the classification methods to be able to classify kelp. Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm...1988). Image processing software for imaging spectrometry analysis. Remote Sensing of Enviroment , 24: 201–210. Perry, C., & Lautenschlager, L. F

Spectral Variability among Rocks in Visible and Near Infrared Multispectral Pancam Data Collected at Gusev Crater: Examinations using Spectral Mixture Analysis and Related Techniques

NASA Technical Reports Server (NTRS)

Farrand, W. H.; Bell, J. F., III; Johnson, J. R.; Squyres, S. W.; Soderblom, J.; Ming, D. W.

2006-01-01

Visible and Near Infrared (VNIR) multispectral observations of rocks made by the Mars Exploration Rover Spirit s Panoramic camera (Pancam) have been analysed using a spectral mixture analysis (SMA) methodology. Scenes have been examined from the Gusev crater plains into the Columbia Hills. Most scenes on the plains and in the Columbia Hills could be modeled as three endmember mixtures of a bright material, rock, and shade. Scenes of rocks disturbed by the rover s Rock Abrasion Tool (RAT) required additional endmembers. In the Columbia Hills there were a number of scenes in which additional rock endmembers were required. The SMA methodology identified relatively dust-free areas on undisturbed rock surfaces, as well as spectrally unique areas on RAT abraded rocks. Spectral parameters from these areas were examined and six spectral classes were identified. These classes are named after a type rock or area and are: Adirondack, Lower West Spur, Clovis, Wishstone, Peace, and Watchtower. These classes are discriminable based, primarily, on near-infrared (NIR) spectral parameters. Clovis and Watchtower class rocks appear more oxidized than Wishstone class rocks and Adirondack basalts based on their having higher 535 nm band depths. Comparison of the spectral parameters of these Gusev crater rocks to parameters of glass-dominated basaltic tuffs indicates correspondence between measurements of Clovis and Watchtower classes, but divergence for the Wishstone class rocks which appear to have a higher fraction of crystalline ferrous iron bearing phases. Despite a high sulfur content, the rock Peace has NIR properties resembling plains basalts.

Effectiveness of Spectral Similarity Measures to Develop Precise Crop Spectra for Hyperspectral Data Analysis

NASA Astrophysics Data System (ADS)

Chauhan, H.; Krishna Mohan, B.

2014-11-01

The present study was undertaken with the objective to check effectiveness of spectral similarity measures to develop precise crop spectra from the collected hyperspectral field spectra. In Multispectral and Hyperspectral remote sensing, classification of pixels is obtained by statistical comparison (by means of spectral similarity) of known field or library spectra to unknown image spectra. Though these algorithms are readily used, little emphasis has been placed on use of various spectral similarity measures to select precise crop spectra from the set of field spectra. Conventionally crop spectra are developed after rejecting outliers based only on broad-spectrum analysis. Here a successful attempt has been made to develop precise crop spectra based on spectral similarity. As unevaluated data usage leads to uncertainty in the image classification, it is very crucial to evaluate the data. Hence, notwithstanding the conventional method, the data precision has been performed effectively to serve the purpose of the present research work. The effectiveness of developed precise field spectra was evaluated by spectral discrimination measures and found higher discrimination values compared to spectra developed conventionally. Overall classification accuracy for the image classified by field spectra selected conventionally is 51.89% and 75.47% for the image classified by field spectra selected precisely based on spectral similarity. KHAT values are 0.37, 0.62 and Z values are 2.77, 9.59 for image classified using conventional and precise field spectra respectively. Reasonable higher classification accuracy, KHAT and Z values shows the possibility of a new approach for field spectra selection based on spectral similarity measure.

SVD analysis of Aura TES spectral residuals

NASA Technical Reports Server (NTRS)

Beer, Reinhard; Kulawik, Susan S.; Rodgers, Clive D.; Bowman, Kevin W.

2005-01-01

Singular Value Decomposition (SVD) analysis is both a powerful diagnostic tool and an effective method of noise filtering. We present the results of an SVD analysis of an ensemble of spectral residuals acquired in September 2004 from a 16-orbit Aura Tropospheric Emission Spectrometer (TES) Global Survey and compare them to alternative methods such as zonal averages. In particular, the technique highlights issues such as the orbital variation of instrument response and incompletely modeled effects of surface emissivity and atmospheric composition.

Analysis of multimode fiber bundles for endoscopic spectral-domain optical coherence tomography

PubMed Central

Risi, Matthew D.; Makhlouf, Houssine; Rouse, Andrew R.; Gmitro, Arthur F.

2016-01-01

A theoretical analysis of the use of a fiber bundle in spectral-domain optical coherence tomography (OCT) systems is presented. The fiber bundle enables a flexible endoscopic design and provides fast, parallelized acquisition of the OCT data. However, the multimode characteristic of the fibers in the fiber bundle affects the depth sensitivity of the imaging system. A description of light interference in a multimode fiber is presented along with numerical simulations and experimental studies to illustrate the theoretical analysis. PMID:25967012

Expanding Coherent Array Processing to Larger Apertures Using Empirical Matched Field Processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ringdal, F; Harris, D B; Kvaerna, T

2009-07-23

We have adapted matched field processing, a method developed in underwater acoustics to detect and locate targets, to classify transient seismic signals arising from mining explosions. Matched field processing, as we apply it, is an empirical technique, using observations of historic events to calibrate the amplitude and phase structure of wavefields incident upon an array aperture for particular repeating sources. The objective of this project is to determine how broadly applicable the method is and to understand the phenomena that control its performance. We obtained our original results in distinguishing events from ten mines in the Khibiny and Olenegorsk miningmore » districts of the Kola Peninsula, for which we had exceptional ground truth information. In a cross-validation test, some 98.2% of 549 explosions were correctly classified by originating mine using just the Pn observations (2.5-12.5 Hz) on the ARCES array at ranges from 350-410 kilometers. These results were achieved despite the fact that the mines are as closely spaced as 3 kilometers. Such classification performance is significantly better than predicted by the Rayleigh limit. Scattering phenomena account for the increased resolution, as we make clear in an analysis of the information carrying capacity of Pn under two alternative propagation scenarios: free-space propagation and propagation with realistic (actually measured) spatial covariance structure. The increase in information capacity over a wide band is captured by the matched field calibrations and used to separate explosions from very closely-spaced sources. In part, the improvement occurs because the calibrations enable coherent processing at frequencies above those normally considered coherent. We are investigating whether similar results can be expected in different regions, with apertures of increasing scale and for diffuse seismicity. We verified similar performance with the closely-spaced Zapolyarni mines, though discovered that it may be necessary to divide event populations from a single mine into identifiable subpopulations. For this purpose, we perform cluster analysis using matched field statistics calculated on pairs of individual events as a distance metric. In our initial work, calibrations were derived from ensembles of events ranging in number to more than 100. We are considering the performance now of matched field calibrations derived with many fewer events (even, as mentioned, individual events). Since these are high-variance estimates, we are testing the use of cross-channel, multitaper, spectral estimation methods to reduce the variance of calibrations and detection statistics derived from single-event observations. To test the applicability of the technique in a different tectonic region, we have obtained four years of continuous data from 4 Kazakh arrays and are extracting large numbers of event segments. Our initial results using 132 mining explosions recorded by the Makanchi array are similar to those obtained in the European Arctic. Matched field processing clearly separates the explosions from three closely-spaced mines located approximately 400 kilometers from the array, again using waveforms in a band (6-10 Hz) normally considered incoherent for this array. Having reproduced ARCES-type performance with another small aperture array, we have two additional objectives for matched field processing. We will attempt to extend matched field processing to larger apertures: a 200 km aperture (the KNET) and, if data permit, to an aperture comprised of several Kazakh arrays. We also will investigate the potential of developing matched field processing to roughly locate and classify natural seismicity, which is more diffuse than the concentrated sources of mining explosions that we have investigated to date.« less

Evaluating Hyperspectral Imaging of Wetland Vegetation as a Tool for Detecting Estuarine Nutrient Enrichment

DTIC Science & Technology

2008-05-01

the vegetation’s uptake of water column nutrients produces a spectral response; and 3) the spectral and spatial resolutions ...analysis. This allowed us to evaluate these assumptions at the landscape level, by using the high spectral and spatial resolution of the hyperspectral... spatial resolution (2.5 m pixels) HyMap hyperspectral imagery of the entire wetland. After using a hand-held spectrometer to characterize

Error analysis for spectral approximation of the Korteweg-De Vries equation

NASA Technical Reports Server (NTRS)

Maday, Y.; recent years.

1987-01-01

The conservation and convergence properties of spectral Fourier methods for the numerical approximation of the Korteweg-de Vries equation are analyzed. It is proved that the (aliased) collocation pseudospectral method enjoys the same convergence properties as the spectral Galerkin method, which is less effective from the computational point of view. This result provides a precise mathematical answer to a question raised by several authors in recent years.

Spectral stratigraphy

NASA Technical Reports Server (NTRS)

Lang, Harold R.

1991-01-01

A new approach to stratigraphic analysis is described which uses photogeologic and spectral interpretation of multispectral remote sensing data combined with topographic information to determine the attitude, thickness, and lithology of strata exposed at the surface. The new stratigraphic procedure is illustrated by examples in the literature. The published results demonstrate the potential of spectral stratigraphy for mapping strata, determining dip and strike, measuring and correlating stratigraphic sequences, defining lithofacies, mapping biofacies, and interpreting geological structures.

Estimation of spectral kurtosis

NASA Astrophysics Data System (ADS)

Sutawanir

2017-03-01

Rolling bearings are the most important elements in rotating machinery. Bearing frequently fall out of service for various reasons: heavy loads, unsuitable lubrications, ineffective sealing. Bearing faults may cause a decrease in performance. Analysis of bearing vibration signals has attracted attention in the field of monitoring and fault diagnosis. Bearing vibration signals give rich information for early detection of bearing failures. Spectral kurtosis, SK, is a parameter in frequency domain indicating how the impulsiveness of a signal varies with frequency. Faults in rolling bearings give rise to a series of short impulse responses as the rolling elements strike faults, SK potentially useful for determining frequency bands dominated by bearing fault signals. SK can provide a measure of the distance of the analyzed bearings from a healthy one. SK provides additional information given by the power spectral density (psd). This paper aims to explore the estimation of spectral kurtosis using short time Fourier transform known as spectrogram. The estimation of SK is similar to the estimation of psd. The estimation falls in model-free estimation and plug-in estimator. Some numerical studies using simulations are discussed to support the methodology. Spectral kurtosis of some stationary signals are analytically obtained and used in simulation study. Kurtosis of time domain has been a popular tool for detecting non-normality. Spectral kurtosis is an extension of kurtosis in frequency domain. The relationship between time domain and frequency domain analysis is establish through power spectrum-autocovariance Fourier transform. Fourier transform is the main tool for estimation in frequency domain. The power spectral density is estimated through periodogram. In this paper, the short time Fourier transform of the spectral kurtosis is reviewed, a bearing fault (inner ring and outer ring) is simulated. The bearing response, power spectrum, and spectral kurtosis are plotted to visualize the pattern of each fault. Keywords: frequency domain Fourier transform, spectral kurtosis, bearing fault

Using 2D correlation analysis to enhance spectral information available from highly spatially resolved AFM-IR spectra

NASA Astrophysics Data System (ADS)

Marcott, Curtis; Lo, Michael; Hu, Qichi; Kjoller, Kevin; Boskey, Adele; Noda, Isao

2014-07-01

The recent combination of atomic force microscopy and infrared spectroscopy (AFM-IR) has led to the ability to obtain IR spectra with nanoscale spatial resolution, nearly two orders-of-magnitude better than conventional Fourier transform infrared (FT-IR) microspectroscopy. This advanced methodology can lead to significantly sharper spectral features than are typically seen in conventional IR spectra of inhomogeneous materials, where a wider range of molecular environments are coaveraged by the larger sample cross section being probed. In this work, two-dimensional (2D) correlation analysis is used to examine position sensitive spectral variations in datasets of closely spaced AFM-IR spectra. This analysis can reveal new key insights, providing a better understanding of the new spectral information that was previously hidden under broader overlapped spectral features. Two examples of the utility of this new approach are presented. Two-dimensional correlation analysis of a set of AFM-IR spectra were collected at 200-nm increments along a line through a nucleation site generated by remelting a small spot on a thin film of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate). There are two different crystalline carbonyl band components near 1720 cm-1 that sequentially disappear before a band at 1740 cm-1 due to more disordered material appears. In the second example, 2D correlation analysis of a series of AFM-IR spectra spaced every 1 μm of a thin cross section of a bone sample measured outward from an osteon center of bone growth. There are many changes in the amide I and phosphate band contours, suggesting changes in the bone structure are occurring as the bone matures.

The application of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the stratum corneum.

PubMed

Goh, Choon Fu; Craig, Duncan Q M; Hadgraft, Jonathan; Lane, Majella E

2017-02-01

Drug permeation through the intercellular lipids, which pack around and between corneocytes, may be enhanced by increasing the thermodynamic activity of the active in a formulation. However, this may also result in unwanted drug crystallisation on and in the skin. In this work, we explore the combination of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the skin. Ex vivo permeation studies of saturated solutions of diclofenac sodium (DF Na) in two vehicles, propylene glycol (PG) and dimethyl sulphoxide (DMSO), were carried out in porcine ear skin. Tape stripping and ATR-FTIR spectroscopy were conducted simultaneously to collect spectral data as a function of skin depth. Multivariate data analysis was applied to visualise and categorise the spectral data in the region of interest (1700-1500cm -1 ) containing the carboxylate (COO - ) asymmetric stretching vibrations of DF Na. Spectral data showed the redshifts of the COO - asymmetric stretching vibrations for DF Na in the solution compared with solid drug. Similar shifts were evident following application of saturated solutions of DF Na to porcine skin samples. Multivariate data analysis categorised the spectral data based on the spectral differences and drug crystallisation was found to be confined to the upper layers of the skin. This proof-of-concept study highlights the utility of ATR-FTIR spectroscopy in combination with multivariate data analysis as a simple and rapid approach in the investigation of drug deposition in the skin. The approach described here will be extended to the study of other actives for topical application to the skin. Copyright © 2016 Elsevier B.V. All rights reserved.

Hyperspectral image classification by a variable interval spectral average and spectral curve matching combined algorithm

NASA Astrophysics Data System (ADS)

Senthil Kumar, A.; Keerthi, V.; Manjunath, A. S.; Werff, Harald van der; Meer, Freek van der

2010-08-01

Classification of hyperspectral images has been receiving considerable attention with many new applications reported from commercial and military sectors. Hyperspectral images are composed of a large number of spectral channels, and have the potential to deliver a great deal of information about a remotely sensed scene. However, in addition to high dimensionality, hyperspectral image classification is compounded with a coarse ground pixel size of the sensor for want of adequate sensor signal to noise ratio within a fine spectral passband. This makes multiple ground features jointly occupying a single pixel. Spectral mixture analysis typically begins with pixel classification with spectral matching techniques, followed by the use of spectral unmixing algorithms for estimating endmembers abundance values in the pixel. The spectral matching techniques are analogous to supervised pattern recognition approaches, and try to estimate some similarity between spectral signatures of the pixel and reference target. In this paper, we propose a spectral matching approach by combining two schemes—variable interval spectral average (VISA) method and spectral curve matching (SCM) method. The VISA method helps to detect transient spectral features at different scales of spectral windows, while the SCM method finds a match between these features of the pixel and one of library spectra by least square fitting. Here we also compare the performance of the combined algorithm with other spectral matching techniques using a simulated and the AVIRIS hyperspectral data sets. Our results indicate that the proposed combination technique exhibits a stronger performance over the other methods in the classification of both the pure and mixed class pixels simultaneously.

Dynamics of modulated beams in spectral domain

DOE PAGES

Yampolsky, Nikolai A.

2017-07-16

General formalism for describing dynamics of modulated beams along linear beamlines is developed. We describe modulated beams with spectral distribution function which represents Fourier transform of the conventional beam distribution function in the 6-dimensional phase space. The introduced spectral distribution function is localized in some region of the spectral domain for nearly monochromatic modulations. It can be characterized with a small number of typical parameters such as the lowest order moments of the spectral distribution. We study evolution of the modulated beams in linear beamlines and find that characteristic spectral parameters transform linearly. The developed approach significantly simplifies analysis ofmore » various schemes proposed for seeding X-ray free electron lasers. We use this approach to study several recently proposed schemes and find the bandwidth of the output bunching in each case.« less

Application of the Spectral Element Method to Acoustic Radiation

NASA Technical Reports Server (NTRS)

Doyle, James F.; Rizzi, Stephen A. (Technical Monitor)

2000-01-01

This report summarizes research to develop a capability for analysis of interior noise in enclosed structures when acoustically excited by an external random source. Of particular interest was the application to the study of noise and vibration transmission in thin-walled structures as typified by aircraft fuselages. Three related topics are focused upon. The first concerns the development of a curved frame spectral element, the second shows how the spectral element method for wave propagation in folded plate structures is extended to problems involving curved segmented plates. These are of significance because by combining these curved spectral elements with previously presented flat spectral elements, the dynamic response of geometrically complex structures can be determined. The third topic shows how spectral elements, which incorporate the effect of fluid loading on the structure, are developed for analyzing acoustic radiation from dynamically loaded extended plates.

Application of spectral methods for high-frequency financial data to quantifying states of market participants

NASA Astrophysics Data System (ADS)

Sato, Aki-Hiro

2008-06-01

Empirical analysis of the foreign exchange market is conducted based on methods to quantify similarities among multi-dimensional time series with spectral distances introduced in [A.-H. Sato, Physica A 382 (2007) 258-270]. As a result it is found that the similarities among currency pairs fluctuate with the rotation of the earth, and that the similarities among best quotation rates are associated with those among quotation frequencies. Furthermore, it is shown that the Jensen-Shannon spectral divergence is proportional to a mean of the Kullback-Leibler spectral distance both empirically and numerically. It is confirmed that these spectral distances are connected with distributions for behavioural parameters of the market participants from numerical simulation. This concludes that spectral distances of representative quantities of financial markets are related into diversification of behavioural parameters of the market participants.

CHROMATOGRAPHIC AND MASS SPECTRAL STUDIES OF PERFLUOROOCTANESULFONATE AND THREE PERFLUOROOCTANESULFONAMIDES

EPA Science Inventory

The chromatographic and mass spectral characteristics of perfluorooctanesulfonate (PFOS) and three nitrogen-substituted perfluorooctanesulfonamides have been obtained. A methyl/phenol mixed phase fused silica capillary column was used for GC analysis, while a C18 reversed phase ...

Spectral Analysis and Experimental Modeling of Ice Accretion Roughness

NASA Technical Reports Server (NTRS)

Orr, D. J.; Breuer, K. S.; Torres, B. E.; Hansman, R. J., Jr.

1996-01-01

A self-consistent scheme for relating wind tunnel ice accretion roughness to the resulting enhancement of heat transfer is described. First, a spectral technique of quantitative analysis of early ice roughness images is reviewed. The image processing scheme uses a spectral estimation technique (SET) which extracts physically descriptive parameters by comparing scan lines from the experimentally-obtained accretion images to a prescribed test function. Analysis using this technique for both streamwise and spanwise directions of data from the NASA Lewis Icing Research Tunnel (IRT) are presented. An experimental technique is then presented for constructing physical roughness models suitable for wind tunnel testing that match the SET parameters extracted from the IRT images. The icing castings and modeled roughness are tested for enhancement of boundary layer heat transfer using infrared techniques in a "dry" wind tunnel.

A distributed microcomputer-controlled system for data acquisition and power spectral analysis of EEG.

PubMed

Vo, T D; Dwyer, G; Szeto, H H

1986-04-01

A relatively powerful and inexpensive microcomputer-based system for the spectral analysis of the EEG is presented. High resolution and speed is achieved with the use of recently available large-scale integrated circuit technology with enhanced functionality (INTEL Math co-processors 8087) which can perform transcendental functions rapidly. The versatility of the system is achieved with a hardware organization that has distributed data acquisition capability performed by the use of a microprocessor-based analog to digital converter with large resident memory (Cyborg ISAAC-2000). Compiled BASIC programs and assembly language subroutines perform on-line or off-line the fast Fourier transform and spectral analysis of the EEG which is stored as soft as well as hard copy. Some results obtained from test application of the entire system in animal studies are presented.

An Excel‐based implementation of the spectral method of action potential alternans analysis

PubMed Central

Pearman, Charles M.

2014-01-01

Abstract Action potential (AP) alternans has been well established as a mechanism of arrhythmogenesis and sudden cardiac death. Proper interpretation of AP alternans requires a robust method of alternans quantification. Traditional methods of alternans analysis neglect higher order periodicities that may have greater pro‐arrhythmic potential than classical 2:1 alternans. The spectral method of alternans analysis, already widely used in the related study of microvolt T‐wave alternans, has also been used to study AP alternans. Software to meet the specific needs of AP alternans analysis is not currently available in the public domain. An AP analysis tool is implemented here, written in Visual Basic for Applications and using Microsoft Excel as a shell. This performs a sophisticated analysis of alternans behavior allowing reliable distinction of alternans from random fluctuations, quantification of alternans magnitude, and identification of which phases of the AP are most affected. In addition, the spectral method has been adapted to allow detection and quantification of higher order regular oscillations. Analysis of action potential morphology is also performed. A simple user interface enables easy import, analysis, and export of collated results. PMID:25501439

Hilbert-Huang Transform: A Spectral Analysis Tool Applied to Sunspot Number and Total Solar Irradiance Variations, as well as Near-Surface Atmospheric Variables

NASA Astrophysics Data System (ADS)

Barnhart, B. L.; Eichinger, W. E.; Prueger, J. H.

2010-12-01

Hilbert-Huang transform (HHT) is a relatively new data analysis tool which is used to analyze nonstationary and nonlinear time series data. It consists of an algorithm, called empirical mode decomposition (EMD), which extracts the cyclic components embedded within time series data, as well as Hilbert spectral analysis (HSA) which displays the time and frequency dependent energy contributions from each component in the form of a spectrogram. The method can be considered a generalized form of Fourier analysis which can describe the intrinsic cycles of data with basis functions whose amplitudes and phases may vary with time. The HHT will be introduced and compared to current spectral analysis tools such as Fourier analysis, short-time Fourier analysis, wavelet analysis and Wigner-Ville distributions. A number of applications are also presented which demonstrate the strengths and limitations of the tool, including analyzing sunspot number variability and total solar irradiance proxies as well as global averaged temperature and carbon dioxide concentration. Also, near-surface atmospheric quantities such as temperature and wind velocity are analyzed to demonstrate the nonstationarity of the atmosphere.

Polychromatic spectral pattern analysis of ultra-weak photon emissions from a human body.

PubMed

Kobayashi, Masaki; Iwasa, Torai; Tada, Mika

2016-06-01

Ultra-weak photon emission (UPE), often designated as biophoton emission, is generally observed in a wide range of living organisms, including human beings. This phenomenon is closely associated with reactive oxygen species (ROS) generated during normal metabolic processes and pathological states induced by oxidative stress. Application of UPE extracting the pathophysiological information has long been anticipated because of its potential non-invasiveness, facilitating its diagnostic use. Nevertheless, its weak intensity and UPE mechanism complexity hinder its use for practical applications. Spectroscopy is crucially important for UPE analysis. However, filter-type spectroscopy technique, used as a conventional method for UPE analysis, intrinsically limits its performance because of its monochromatic scheme. To overcome the shortcomings of conventional methods, the authors developed a polychromatic spectroscopy system for UPE spectral pattern analysis. It is based on a highly efficient lens systems and a transmission-type diffraction grating with a highly sensitive, cooled, charge-coupled-device (CCD) camera. Spectral pattern analysis of the human body was done for a fingertip using the developed system. The UPE spectrum covers the spectral range of 450-750nm, with a dominant emission region of 570-670nm. The primary peak is located in the 600-650nm region. Furthermore, application of UPE source exploration was demonstrated with the chemiluminescence spectrum of melanin and coexistence with oxidized linoleic acid. Copyright © 2016 Elsevier B.V. All rights reserved.

Airborne spectroradiometry: The application of AIS data to detecting subtle mineral absorption features

NASA Technical Reports Server (NTRS)

Cocks, T. D.; Green, A. A.

1986-01-01

Analysis of Airborne Imaging Spectrometer (AIS) data acquired in Australia has revealed a number of operational problems. Horizontal striping in AIS imagery and spectral distortions due to order overlap were investigated. Horizontal striping, caused by grating position errors can be removed with little or no effect on spectral details. Order overlap remains a problem that seriously compromises identification of subtle mineral absorption features within AIS spectra. A spectrometric model of the AIS was developed to assist in identifying spurious spectral features, and will be used in efforts to restore the spectral integrity of the data.

Spectral long-range interaction of temporal incoherent solitons.

PubMed

Xu, Gang; Garnier, Josselin; Picozzi, Antonio

2014-02-01

We study the interaction of temporal incoherent solitons sustained by a highly noninstantaneous (Raman-like) nonlinear response. The incoherent solitons exhibit a nonmutual interaction, which can be either attractive or repulsive depending on their relative initial distance. The analysis reveals that incoherent solitons exhibit a long-range interaction in frequency space, which is in contrast with the expected spectral short-range interaction described by the usual approach based on the Raman-like spectral gain curve. Both phenomena of anomalous interaction and spectral long-range behavior of incoherent solitons are described in detail by a long-range Vlasov equation.

Determination of spectral signatures of substances in natural waters

NASA Technical Reports Server (NTRS)

Klemas, V.; Philpot, W. D.; Davis, G.

1978-01-01

Optical remote sensing of water pollution offers the possibility of fast, large scale coverage at a relatively low cost. The possibility of using the spectral characteristics of the upwelling light from water for the purpose of ocean water quality monitoring was explained. The work was broken into several broad tasks as follows: (1) definition of a remotely measured spectral signature of water, (2) collection of field data and testing of the signature analysis, and (3) the possibility of using LANDSAT data for the identification of substances in water. An attempt to extract spectral signatures of acid waste and sediment was successful.

A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis

PubMed Central

Hsieh, Sheng-Hsun; Wang, Wei; Tien, Chung-Hao

2018-01-01

In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL) pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR) was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme. PMID:29509692

Spectral Analysis of the sdO Standard Star Feige 34

NASA Astrophysics Data System (ADS)

Latour, M.; Chayer, P.; Green, E. M.; Fontaine, G.

2017-03-01

We present our current work on the spectral analysis of the hot sdO star Feige 34. We combine high S/N optical spectra and fully-blanketed non-LTE model atmospheres to derive its fundamental parameters (Teff, log g) and helium abundance. Our best fits indicate Teff = 63 000 K, log g = 6.0 and log N(He)/N(H) = -1.8. We also use available ultraviolet spectra (IUE and FUSE) to measure metal abundances. We find the star to be enriched in iron and nickel by a factor of ten with respect to the solar values, while lighter elements have subsolar abundances. The FUSE spectrum suggests that the spectral lines could be broadened by rotation.

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

Reconstructing spectral cues for sound localization from responses to rippled noise stimuli

PubMed Central

Vliegen, Joyce; Van Esch, Thamar

2017-01-01

Human sound localization in the mid-saggital plane (elevation) relies on an analysis of the idiosyncratic spectral shape cues provided by the head and pinnae. However, because the actual free-field stimulus spectrum is a-priori unknown to the auditory system, the problem of extracting the elevation angle from the sensory spectrum is ill-posed. Here we test different spectral localization models by eliciting head movements toward broad-band noise stimuli with randomly shaped, rippled amplitude spectra emanating from a speaker at a fixed location, while varying the ripple bandwidth between 1.5 and 5.0 cycles/octave. Six listeners participated in the experiments. From the distributions of localization responses toward the individual stimuli, we estimated the listeners’ spectral-shape cues underlying their elevation percepts, by applying maximum-likelihood estimation. The reconstructed spectral cues resulted to be invariant to the considerable variation in ripple bandwidth, and for each listener they had a remarkable resemblance to the idiosyncratic head-related transfer functions (HRTFs). These results are not in line with models that rely on the detection of a single peak or notch in the amplitude spectrum, nor with a local analysis of first- and second-order spectral derivatives. Instead, our data support a model in which the auditory system performs a cross-correlation between the sensory input at the eardrum-auditory nerve, and stored representations of HRTF spectral shapes, to extract the perceived elevation angle. PMID:28333967

Quantile regression applied to spectral distance decay

USGS Publications Warehouse

Rocchini, D.; Cade, B.S.

2008-01-01

Remotely sensed imagery has long been recognized as a powerful support for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance allows us to quantitatively estimate the amount of turnover in species composition with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological data sets are characterized by a high number of zeroes that add noise to the regression model. Quantile regressions can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this letter, we used ordinary least squares (OLS) and quantile regressions to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.01), considering both OLS and quantile regressions. Nonetheless, the OLS regression estimate of the mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when the spectral distance approaches zero, was very low compared with the intercepts of the upper quantiles, which detected high species similarity when habitats are more similar. In this letter, we demonstrated the power of using quantile regressions applied to spectral distance decay to reveal species diversity patterns otherwise lost or underestimated by OLS regression. ?? 2008 IEEE.

Spectral distance decay: Assessing species beta-diversity by quantile regression

USGS Publications Warehouse

Rocchinl, D.; Nagendra, H.; Ghate, R.; Cade, B.S.

2009-01-01

Remotely sensed data represents key information for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance may allow us to quantitatively estimate how beta-diversity in species changes with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological datasets are characterized by a high number of zeroes that can add noise to the regression model. Quantile regression can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this paper, we used ordinary least square (ols) and quantile regression to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.05) considering both ols and quantile regression. Nonetheless, ols regression estimate of mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when spectral distance approaches zero, was very low compared with the intercepts of upper quantiles, which detected high species similarity when habitats are more similar. In this paper we demonstrated the power of using quantile regressions applied to spectral distance decay in order to reveal species diversity patterns otherwise lost or underestimated by ordinary least square regression. ?? 2009 American Society for Photogrammetry and Remote Sensing.

Univariate and multivariate molecular spectral analyses of lipid related molecular structural components in relation to nutrient profile in feed and food mixtures.

PubMed

Abeysekara, Saman; Damiran, Daalkhaijav; Yu, Peiqiang

2013-02-01

The objectives of this study were (i) to determine lipid related molecular structures components (functional groups) in feed combination of cereal grain (barley, Hordeum vulgare) and wheat (Triticum aestivum) based dried distillers grain solubles (wheat DDGSs) from bioethanol processing at five different combination ratios using univariate and multivariate molecular spectral analyses with infrared Fourier transform molecular spectroscopy, and (ii) to correlate lipid-related molecular-functional structure spectral profile to nutrient profiles. The spectral intensity of (i) CH(3) asymmetric, CH(2) asymmetric, CH(3) symmetric and CH(2) symmetric groups, (ii) unsaturation (CC) group, and (iii) carbonyl ester (CO) group were determined. Spectral differences of functional groups were detected by hierarchical cluster analysis (HCA) and principal components analysis (PCA). The results showed that the combination treatments significantly inflicted modifications (P<0.05) in nutrient profile and lipid related molecular spectral intensity (CH(2) asymmetric stretching peak height, CH(2) symmetric stretching peak height, ratio of CH(2) to CH(3) symmetric stretching peak intensity, and carbonyl peak area). Ratio of CH(2) to CH(3) symmetric stretching peak intensity, and carbonyl peak significantly correlated with nutrient profiles. Both PCA and HCA differentiated lipid-related spectrum. In conclusion, the changes of lipid molecular structure spectral profiles through feed combination could be detected using molecular spectroscopy. These changes were associated with nutrient profiles and functionality. Copyright © 2012 Elsevier B.V. All rights reserved.

Photoplethysmographic imaging via spectrally demultiplexed erythema fluctuation analysis for remote heart rate monitoring

NASA Astrophysics Data System (ADS)

Deglint, Jason; Chung, Audrey G.; Chwyl, Brendan; Amelard, Robert; Kazemzadeh, Farnoud; Wang, Xiao Yu; Clausi, David A.; Wong, Alexander

2016-03-01

Traditional photoplethysmographic imaging (PPGI) systems use the red, green, and blue (RGB) broadband measurements of a consumer digital camera to remotely estimate a patients heart rate; however, these broadband RGB signals are often corrupted by ambient noise, making the extraction of subtle fluctuations indicative of heart rate difficult. Therefore, the use of narrow-band spectral measurements can significantly improve the accuracy. We propose a novel digital spectral demultiplexing (DSD) method to infer narrow-band spectral information from acquired broadband RGB measurements in order to estimate heart rate via the computation of motion- compensated skin erythema fluctuation. Using high-resolution video recordings of human participants, multiple measurement locations are automatically identified on the cheeks of an individual, and motion-compensated broadband reflectance measurements are acquired at each measurement location over time via measurement location tracking. The motion-compensated broadband reflectance measurements are spectrally demultiplexed using a non-linear inverse model based on the spectral sensitivity of the camera's detector. A PPG signal is then computed from the demultiplexed narrow-band spectral information via skin erythema fluctuation analysis, with improved signal-to-noise ratio allowing for reliable remote heart rate measurements. To assess the effectiveness of the proposed system, a set of experiments involving human motion in a front-facing position were performed under ambient lighting conditions. Experimental results indicate that the proposed system achieves robust and accurate heart rate measurements and can provide additional information about the participant beyond the capabilities of traditional PPGI methods.

Temporal scaling of groundwater level fluctuations near a stream

USGS Publications Warehouse

Schilling, K.E.; Zhang, Y.-K.

2012-01-01

Temporal scaling in stream discharge and hydraulic heads in riparian wells was evaluated to determine the feasibility of using spectral analysis to identify potential surface and groundwater interaction. In floodplains where groundwater levels respond rapidly to precipitation recharge, potential interaction is established if the hydraulic head (h) spectrum of riparian groundwater has a power spectral density similar to stream discharge (Q), exhibiting a characteristic breakpoint between high and low frequencies. At a field site in Walnut Creek watershed in central Iowa, spectral analysis of h in wells located 1 m from the channel edge showed a breakpoint in scaling very similar to the spectrum of Q (~20 h), whereas h in wells located 20 and 40 m from the channel showed temporal scaling from 1 to 10,000 h without a well-defined breakpoint. The spectral exponent (??) in the riparian zone decreased systematically from the channel into the floodplain as groundwater levels were increasingly dominated by white noise groundwater recharge. The scaling pattern of hydraulic head was not affected by land cover type, although the number of analyses was limited and site conditions were variable among sites. Spectral analysis would not replace quantitative tracer or modeling studies, but the method may provide a simple means of confirming potential interaction at some sites. ?? 2011, The Author(s). Ground Water ?? 2011, National Ground Water Association.

Temporal scaling of groundwater level fluctuations near a stream.

PubMed

Schilling, Keith E; Zhang, You-Kuan

2012-01-01

Temporal scaling in stream discharge and hydraulic heads in riparian wells was evaluated to determine the feasibility of using spectral analysis to identify potential surface and groundwater interaction. In floodplains where groundwater levels respond rapidly to precipitation recharge, potential interaction is established if the hydraulic head (h) spectrum of riparian groundwater has a power spectral density similar to stream discharge (Q), exhibiting a characteristic breakpoint between high and low frequencies. At a field site in Walnut Creek watershed in central Iowa, spectral analysis of h in wells located 1 m from the channel edge showed a breakpoint in scaling very similar to the spectrum of Q (∼20 h), whereas h in wells located 20 and 40 m from the channel showed temporal scaling from 1 to 10,000 h without a well-defined breakpoint. The spectral exponent (β) in the riparian zone decreased systematically from the channel into the floodplain as groundwater levels were increasingly dominated by white noise groundwater recharge. The scaling pattern of hydraulic head was not affected by land cover type, although the number of analyses was limited and site conditions were variable among sites. Spectral analysis would not replace quantitative tracer or modeling studies, but the method may provide a simple means of confirming potential interaction at some sites. © 2011, The Author(s). Ground Water © 2011, National Ground Water Association.

Investigation of surface wave amplitudes in 3-D velocity and 3-D Q models

NASA Astrophysics Data System (ADS)

Ruan, Y.; Zhou, Y.

2010-12-01

It has been long recognized that seismic amplitudes depend on both wave speed structures and anelasticity (Q) structures. However, the effects of lateral heterogeneities in wave speed and Q structures on seismic amplitudes has not been well understood. We investigate the effects of 3-D wave speed and 3-D anelasticity (Q) structures on surface-wave amplitudes based upon wave propagation simulations of twelve globally-distributed earthquakes and 801 stations in Earth models with and without lateral heterogeneities in wave speed and anelasticity using a Spectral Element Method (SEM). Our tomographic-like 3-D Q models are converted from a velocity model S20RTS using a set of reasonable mineralogical parameters, assuming lateral perturbations in both velocity and Q are due to temperature perturbations. Surface-wave amplitude variations of SEM seismograms are measured in the period range of 50--200 s using boxcar taper, cosine taper and Slepian multi-tapers. We calculate ray-theoretical predictions of surface-wave amplitude perturbations due to elastic focusing, attenuation, and anelastic focusing which respectively depend upon the second spatial derivative (''roughness'') of perturbations in phase velocity, 1/Q, and the roughness of perturbations in 1/Q. Both numerical experiments and theoretical calculations show that (1) for short-period (~ 50 s) surface waves, the effects of amplitude attenuation due to 3-D Q structures are comparable with elastic focusing effects due to 3-D wave speed structures; and (2) for long-period (> 100 s) surface waves, the effects of attenuation become much weaker than elastic focusing; and (3) elastic focusing effects are correlated with anelastic focusing at all periods due to the correlation between velocity and Q models; and (4) amplitude perturbations are depend on measurement techniques and therefore cannot be directly compared with ray-theoretical predictions because ray theory does not account for the effects of measurement techniques. We calculate 3-D finite-frequency sensitivity of surface-wave amplitude to perturbations in wave speed and anelasticity (Q) which fully account for the effects of elastic focusing, attenuation, anelastic focusing as well as measurement techniques. We show that amplitude perturbations calculated using wave speed and Q sensitivity kernels agree reasonably well with SEM measurements and therefore the sensitivity kernels can be used in a joint inversion of seismic phase delays and amplitudes to simultaneously image high resolution 3-D wave speed and 3-D Q structures in the upper mantle.

Understanding the spatial distribution of eroded areas in the former rural homelands of South Africa: Comparative evidence from two new non-commercial multispectral sensors

NASA Astrophysics Data System (ADS)

Sepuru, Terrence Koena; Dube, Timothy

2018-07-01

In this study, we determine the most suitable multispectral sensor that can accurately detect and map eroded areas from other land cover types in Sekhukhune rural district, Limpopo Province, South Africa. Specifically, the study tested the ability of multi-date (wet and dry season) Landsat 8 OLI and Sentinel-2 MSI images in detecting and mapping eroded areas. The implementation was done, using a robust non-parametric classification ensemble: Discriminant Analysis (DA). Three sets of analysis were applied (Analysis 1: Spectral bands as independent dataset; Analysis 2: Spectral vegetation indices as independent and Analysis 3: Combined spectral bands and spectral vegetation indices). Overall classification accuracies ranging between 80% to 81.90% for MSI and 75.71%-80.95% for OLI were derived for the wet and dry season, respectively. The integration of spectral bands and spectral vegetation indices showed that Sentinel-2 (OA = 83, 81%), slightly performed better than Landsat 8, with 82, 86%. The use of bands and vegetation indices as independent dataset resulted in slightly weaker results for both sensors. Sentinel-2 MSI bands located in the NIR (0.785-0.900 μm), red edge (0.698-0.785 μm) and SWIR (1.565-2.280 μm) regions were selected as the most optimal for discriminating degraded soils from other land cover types. However, for Landsat 8OLI, only the SWIR (1.560-2.300 μm), NIR (0.845-0.885 μm) region were selected as the best regions. Of the eighteen spectral vegetation indices computed, NDVI and SAVI and SAVI and Global Environmental Monitoring Index (GEMI) were ranked selected as the most suitable for detecting and mapping soil erosion. Additionally, SRTM DEM derived information illustrates that for both sensors eroded areas occur on sites that are 600 m and 900 m of altitude with similar trends observed in both dry and wet season maps. Findings of this work emphasize the importance of free and readily available new generation sensors in continuous landscape-scale soil erosion monitoring. Besides, such information can help to identify hotspots and potentially vulnerable areas, as well as aid in developing possible control and mitigation measures.

Multi-site recording and spectral analysis of spontaneous photon emission from human body.

PubMed

Wijk, Eduard P A Van; Wijk, Roeland Van

2005-04-01

In the past years, research on ultraweak photon emission (UPE) from human body has increased for isolated cells and tissues. However, there are only limited data on UPE from the whole body, in particular from the hands. To describe a protocol for the management of subjects that (1) avoids interference with light-induced longterm delayed luminescence, and (2) includes the time slots for recording photon emission. The protocol was utilised for multi-site recording of 4 subjects at different times of the day and different seasons, and for one subject to complete spectral analysis of emission from different body locations. An especially selected low-noise end-window photomultiplier was utilised for the detection of ultraviolet / visible light (200-650 nm) photon emission. For multi-site recording it was manipulated in three directions in a darkroom with a very low count rate. A series of cut-off filters was used for spectral analysis of UPE. 29 body sites were selected such that the distribution in UPE could be studied as right-left symmetry, dorsal-ventral symmetry, and the ratio between the central body part and extremities. Generally, the fluctuation in photon counts over the body was lower in the morning than in the afternoon. The thorax-abdomen region emitted lowest and most constantly. The upper extremities and the head region emitted most and increasingly over the day. Spectral analysis of low, intermediate and high emission from the superior frontal part of the right leg, the forehead and the palms in the sensitivity range of the photomultiplier showed the major spontaneous emission at 470-570 nm. The central palm area of hand emission showed a larger contribution of the 420-470 nm range in the spectrum of spontaneous emission from the hand in autumn/winter. The spectrum of delayed luminescence from the hand showed major emission in the same range as spontaneous emission. Examples of multi-site UPE recordings and spectral analysis revealed individual patterns and dynamics of spontaneous UPE over the body, and spectral differences over the body. The spectral data suggest that measurements might well provide quantitative data on the individual pattern of peroxidative and anti-oxidative processes in vivo. We expect that the measurements provide physiological information that can be useful in clinical examination.

Ventilatory thresholds determined from HRV: comparison of 2 methods in obese adolescents.

PubMed

Quinart, S; Mourot, L; Nègre, V; Simon-Rigaud, M-L; Nicolet-Guénat, M; Bertrand, A-M; Meneveau, N; Mougin, F

2014-03-01

The development of personalised training programmes is crucial in the management of obesity. We evaluated the ability of 2 heart rate variability analyses to determine ventilatory thresholds (VT) in obese adolescents. 20 adolescents (mean age 14.3±1.6 years and body mass index z-score 4.2±0.1) performed an incremental test to exhaustion before and after a 9-month multidisciplinary management programme. The first (VT1) and second (VT2) ventilatory thresholds were identified by the reference method (gas exchanges). We recorded RR intervals to estimate VT1 and VT2 from heart rate variability using time-domain analysis and time-varying spectral-domain analysis. The coefficient correlations between thresholds were higher with spectral-domain analysis compared to time-domain analysis: Heart rate at VT1: r=0.91 vs. =0.66 and VT2: r=0.91 vs. =0.66; power at VT1: r=0.91 vs. =0.74 and VT2: r=0.93 vs. =0.78; spectral-domain vs. time-domain analysis respectively). No systematic bias in heart rate at VT1 and VT2 with standard deviations <6 bpm were found, confirming that spectral-domain analysis could replace the reference method for the detection of ventilatory thresholds. Furthermore, this technique is sensitive to rehabilitation and re-training, which underlines its utility in clinical practice. This inexpensive and non-invasive tool is promising for prescribing physical activity programs in obese adolescents. © Georg Thieme Verlag KG Stuttgart · New York.

[Study on Application of NIR Spectral Information Screening in Identification of Maca Origin].

PubMed

Wang, Yuan-zhong; Zhao, Yan-li; Zhang, Ji; Jin, Hang

2016-02-01

Medicinal and edible plant Maca is rich in various nutrients and owns great medicinal value. Based on near infrared diffuse reflectance spectra, 139 Maca samples collected from Peru and Yunnan were used to identify their geographical origins. Multiplication signal correction (MSC) coupled with second derivative (SD) and Norris derivative filter (ND) was employed in spectral pretreatment. Spectrum range (7,500-4,061 cm⁻¹) was chosen by spectrum standard deviation. Combined with principal component analysis-mahalanobis distance (PCA-MD), the appropriate number of principal components was selected as 5. Based on the spectrum range and the number of principal components selected, two abnormal samples were eliminated by modular group iterative singular sample diagnosis method. Then, four methods were used to filter spectral variable information, competitive adaptive reweighted sampling (CARS), monte carlo-uninformative variable elimination (MC-UVE), genetic algorithm (GA) and subwindow permutation analysis (SPA). The spectral variable information filtered was evaluated by model population analysis (MPA). The results showed that RMSECV(SPA) > RMSECV(CARS) > RMSECV(MC-UVE) > RMSECV(GA), were 2. 14, 2. 05, 2. 02, and 1. 98, and the spectral variables were 250, 240, 250 and 70, respectively. According to the spectral variable filtered, partial least squares discriminant analysis (PLS-DA) was used to build the model, with random selection of 97 samples as training set, and the other 40 samples as validation set. The results showed that, R²: GA > MC-UVE > CARS > SPA, RMSEC and RMSEP: GA < MC-UVE < CARS

Fluctuation-Enhanced Sensing for Biological Agent Detection and Identification

DTIC Science & Technology

2009-01-01

method for bacterium detection published earlier; sensing and evaluating the odors of microbes ; and spectral and amplitude distribution analysis of noise...REPORT TYPE 3. DATES COVERED 00-00-2009 to 00-00-2009 4. TITLE AND SUBTITLE Fluctuation-Enhanced Sensing for Biological Agent Detection and...evaluating the odors of microbes ; and spectral and amplitude distribution analysis of noise in light scattering to identify spores based on their

Demonstration of spectral calibration for stellar interferometry

NASA Technical Reports Server (NTRS)

Demers, Richard T.; An, Xin; Tang, Hong; Rud, Mayer; Wayne, Leonard; Kissil, Andrew; Kwack, Eug-Yun

2006-01-01

A breadboard is under development to demonstrate the calibration of spectral errors in microarcsecond stellar interferometers. Analysis shows that thermally and mechanically stable hardware in addition to careful optical design can reduce the wavelength dependent error to tens of nanometers. Calibration of the hardware can further reduce the error to the level of picometers. The results of thermal, mechanical and optical analysis supporting the breadboard design will be shown.

Convergence Analysis of the Graph Allen-Cahn Scheme

DTIC Science & Technology

2016-02-01

CONVERGENCE ANALYSIS OF THE GRAPH ALLEN-CAHN SCHEME ∗ XIYANG LUO† AND ANDREA L. BERTOZZI† Abstract. Graph partitioning problems have a wide range of...optimization, convergence and monotonicity are shown for a class of schemes under a graph-independent timestep restriction. We also analyze the effects of...spectral truncation, a common technique used to save computational cost. Convergence of the scheme with spectral truncation is also proved under a

Signal-to-noise analysis of a birefringent spectral zooming imaging spectrometer

NASA Astrophysics Data System (ADS)

Li, Jie; Zhang, Xiaotong; Wu, Haiying; Qi, Chun

2018-05-01

Study of signal-to-noise ratio (SNR) of a novel spectral zooming imaging spectrometer (SZIS) based on two identical Wollaston prisms is conducted. According to the theory of radiometry and Fourier transform spectroscopy, we deduce the theoretical equations of SNR of SZIS in spectral domain with consideration of the incident wavelength and the adjustable spectral resolution. An example calculation of SNR of SZIS is performed over 400-1000 nm. The calculation results indicate that SNR with different spectral resolutions of SZIS can be optionally selected by changing the spacing between the two identical Wollaston prisms. This will provide theoretical basis for the design, development and engineering of the developed imaging spectrometer for broad spectrum and SNR requirements.

Spectral properties of the massless relativistic quartic oscillator

NASA Astrophysics Data System (ADS)

Durugo, Samuel O.; Lőrinczi, József

2018-03-01

An explicit solution of the spectral problem of the non-local Schrödinger operator obtained as the sum of the square root of the Laplacian and a quartic potential in one dimension is presented. The eigenvalues are obtained as zeroes of special functions related to the fourth order Airy function, and closed formulae for the Fourier transform of the eigenfunctions are derived. These representations allow to derive further spectral properties such as estimates of spectral gaps, heat trace and the asymptotic distribution of eigenvalues, as well as a detailed analysis of the eigenfunctions. A subtle spectral effect is observed which manifests in an exponentially tight approximation of the spectrum by the zeroes of the dominating term in the Fourier representation of the eigenfunctions and its derivative.

Robust Multipoint Water-Fat Separation Using Fat Likelihood Analysis

PubMed Central

Yu, Huanzhou; Reeder, Scott B.; Shimakawa, Ann; McKenzie, Charles A.; Brittain, Jean H.

2016-01-01

Fat suppression is an essential part of routine MRI scanning. Multiecho chemical-shift based water-fat separation methods estimate and correct for Bo field inhomogeneity. However, they must contend with the intrinsic challenge of water-fat ambiguity that can result in water-fat swapping. This problem arises because the signals from two chemical species, when both are modeled as a single discrete spectral peak, may appear indistinguishable in the presence of Bo off-resonance. In conventional methods, the water-fat ambiguity is typically removed by enforcing field map smoothness using region growing based algorithms. In reality, the fat spectrum has multiple spectral peaks. Using this spectral complexity, we introduce a novel concept that identifies water and fat for multiecho acquisitions by exploiting the spectral differences between water and fat. A fat likelihood map is produced to indicate if a pixel is likely to be water-dominant or fat-dominant by comparing the fitting residuals of two different signal models. The fat likelihood analysis and field map smoothness provide complementary information, and we designed an algorithm (Fat Likelihood Analysis for Multiecho Signals) to exploit both mechanisms. It is demonstrated in a wide variety of data that the Fat Likelihood Analysis for Multiecho Signals algorithm offers highly robust water-fat separation for 6-echo acquisitions, particularly in some previously challenging applications. PMID:21842498

Separation of β-amyloid binding and white matter uptake of 18F-flutemetamol using spectral analysis

PubMed Central

Heurling, Kerstin; Buckley, Christopher; Vandenberghe, Rik; Laere, Koen Van; Lubberink, Mark

2015-01-01

The kinetic components of the β-amyloid ligand 18F-flutemetamol binding in grey and white matter were investigated through spectral analysis, and a method developed for creation of parametric images separating grey and white matter uptake. Tracer uptake in grey and white matter and cerebellar cortex was analyzed through spectral analysis in six subjects, with (n=4) or without (n=2) apparent β-amyloid deposition, having undergone dynamic 18F-flutemetamol scanning with arterial blood sampling. The spectra were divided into three components: slow, intermediate and fast basis function rates. The contribution of each of the components to total volume of distribution (VT) was assessed for different tissue types. The slow component dominated in white matter (average 90%), had a higher contribution to grey matter VT in subjects with β-amyloid deposition (average 44%) than without (average 6%) and was absent in cerebellar cortex, attributing the slow component of 18F-flutemetamol uptake in grey matter to β-amyloid binding. Parametric images of voxel-based spectral analysis were created for VT, the slow component and images segmented based on the slow component contribution; confirming that grey matter and white matter uptake can be discriminated on voxel-level using a threshold for the contribution from the slow component to VT. PMID:26550542

Ocean wavenumber estimation from wave-resolving time series imagery

USGS Publications Warehouse

Plant, N.G.; Holland, K.T.; Haller, M.C.

2008-01-01

We review several approaches that have been used to estimate ocean surface gravity wavenumbers from wave-resolving remotely sensed image sequences. Two fundamentally different approaches that utilize these data exist. A power spectral density approach identifies wavenumbers where image intensity variance is maximized. Alternatively, a cross-spectral correlation approach identifies wavenumbers where intensity coherence is maximized. We develop a solution to the latter approach based on a tomographic analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency and can be applied to arbitrary sampling patterns, as well as to full-frame imagery. The solution includes error predictions that can be used for data retrieval quality control and for evaluating sample designs. A quantitative analysis of the intrinsic resolution of the method indicates that the cross-spectral correlation fitting improves resolution by a factor of about ten times as compared to the power spectral density fitting approach. The resolution analysis also provides a rule of thumb for nearshore bathymetry retrievals-short-scale cross-shore patterns may be resolved if they are about ten times longer than the average water depth over the pattern. This guidance can be applied to sample design to constrain both the sensor array (image resolution) and the analysis array (tomographic resolution). ?? 2008 IEEE.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures.

PubMed

Tibau, Elisenda; Valencia, Miguel; Soriano, Jordi

2013-01-01

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

Direct comparison of low- and mid-frequency Raman spectroscopy for quantitative solid-state pharmaceutical analysis.

PubMed

Lipiäinen, Tiina; Fraser-Miller, Sara J; Gordon, Keith C; Strachan, Clare J

2018-02-05

This study considers the potential of low-frequency (terahertz) Raman spectroscopy in the quantitative analysis of ternary mixtures of solid-state forms. Direct comparison between low-frequency and mid-frequency spectral regions for quantitative analysis of crystal form mixtures, without confounding sampling and instrumental variations, is reported for the first time. Piroxicam was used as a model drug, and the low-frequency spectra of piroxicam forms β, α2 and monohydrate are presented for the first time. These forms show clear spectral differences in both the low- and mid-frequency regions. Both spectral regions provided quantitative models suitable for predicting the mixture compositions using partial least squares regression (PLSR), but the low-frequency data gave better models, based on lower errors of prediction (2.7, 3.1 and 3.2% root-mean-square errors of prediction [RMSEP] values for the β, α2 and monohydrate forms, respectively) than the mid-frequency data (6.3, 5.4 and 4.8%, for the β, α2 and monohydrate forms, respectively). The better performance of low-frequency Raman analysis was attributed to larger spectral differences between the solid-state forms, combined with a higher signal-to-noise ratio. Copyright © 2017 Elsevier B.V. All rights reserved.

Spectral reflectance characteristics of soils in northeastern Brazil as influenced by salinity levels.

PubMed

Pessoa, Luiz Guilherme Medeiros; Freire, Maria Betânia Galvão Dos Santos; Wilcox, Bradford Paul; Green, Colleen Heather Machado; De Araújo, Rômulo José Tolêdo; De Araújo Filho, José Coelho

2016-11-01

In northeastern Brazil, large swaths of once-productive soils have been severely degraded by soil salinization, but the true extent of the damage has not been assessed. Emerging remote sensing technology based on hyperspectral analysis offers one possibility for large-scale assessment, but it has been unclear to what extent the spectral properties of soils are related to salinity characteristics. The purpose of this study was to characterize the spectral properties of degraded (saline) and non-degraded agricultural soils in northeastern Brazil and determine the extent to which these properties correspond to soil salinity. We took soil samples from 78 locations within a 45,000-km 2 site in Pernambuco State. We used cluster analysis to group the soil samples on the basis of similarities in salinity and sodicity levels, and then obtained spectral data for each group. The physical properties analysis indicated a predominance of the coarse sand fraction in almost all the soil groups, and total porosity was similar for all the groups. The chemical analysis revealed different levels of degradation among the groups, ranging from non-degraded to strongly degraded conditions, as defined by the degree of salinity and sodicity. The soil properties showing the highest correlation with spectral reflectance were the exchangeable sodium percentage followed by fine sand. Differences in the reflectance curves for the various soil groups were relatively small and were not significant. These results suggest that, where soil crusts are not present, significant challenges remain for using hyperspectral remote sensing to assess soil salinity in northeastern Brazil.

Comparison of existing digital image analysis systems for the analysis of Thematic Mapper data

NASA Technical Reports Server (NTRS)

Likens, W. C.; Wrigley, R. C.

1984-01-01

Most existing image analysis systems were designed with the Landsat Multi-Spectral Scanner in mind, leaving open the question of whether or not these systems could adequately process Thematic Mapper data. In this report, both hardware and software systems have been evaluated for compatibility with TM data. Lack of spectral analysis capability was not found to be a problem, though techniques for spatial filtering and texture varied. Computer processing speed and data storage of currently existing mini-computer based systems may be less than adequate. Upgrading to more powerful hardware may be required for many TM applications.

Impact of JPEG2000 compression on spatial-spectral endmember extraction from hyperspectral data

NASA Astrophysics Data System (ADS)

Martín, Gabriel; Ruiz, V. G.; Plaza, Antonio; Ortiz, Juan P.; García, Inmaculada

2009-08-01

Hyperspectral image compression has received considerable interest in recent years. However, an important issue that has not been investigated in the past is the impact of lossy compression on spectral mixture analysis applications, which characterize mixed pixels in terms of a suitable combination of spectrally pure spectral substances (called endmembers) weighted by their estimated fractional abundances. In this paper, we specifically investigate the impact of JPEG2000 compression of hyperspectral images on the quality of the endmembers extracted by algorithms that incorporate both the spectral and the spatial information (useful for incorporating contextual information in the spectral endmember search). The two considered algorithms are the automatic morphological endmember extraction (AMEE) and the spatial spectral endmember extraction (SSEE) techniques. Experimental results are conducted using a well-known data set collected by AVIRIS over the Cuprite mining district in Nevada and with detailed ground-truth information available from U. S. Geological Survey. Our experiments reveal some interesting findings that may be useful to specialists applying spatial-spectral endmember extraction algorithms to compressed hyperspectral imagery.

Analysis of Spectral Features of Seawaterbiooptical Components Fluorescence from the Excitation-emission Matrix

NASA Astrophysics Data System (ADS)

Salyuk, P. A.; Nagorny, I. G.

The paper presents the method for processing of excitation-emission matrix of sea water and the allocation of the spectral characteristics of different types of colored dissolved organic matter (CDOM) and phytoplankton cells in seawater. The method consists of identification of regularly observed fluorescence peaks of CDOM in marine waters of different type and definition of the spectral ranges, where the predominant influence of these peaks are observed.

SAR image change detection using watershed and spectral clustering

NASA Astrophysics Data System (ADS)

Niu, Ruican; Jiao, L. C.; Wang, Guiting; Feng, Jie

2011-12-01

A new method of change detection in SAR images based on spectral clustering is presented in this paper. Spectral clustering is employed to extract change information from a pair images acquired on the same geographical area at different time. Watershed transform is applied to initially segment the big image into non-overlapped local regions, leading to reduce the complexity. Experiments results and system analysis confirm the effectiveness of the proposed algorithm.

Spectral imaging: principles and applications.

PubMed

Garini, Yuval; Young, Ian T; McNamara, George

2006-08-01

Spectral imaging extends the capabilities of biological and clinical studies to simultaneously study multiple features such as organelles and proteins qualitatively and quantitatively. Spectral imaging combines two well-known scientific methodologies, namely spectroscopy and imaging, to provide a new advantageous tool. The need to measure the spectrum at each point of the image requires combining dispersive optics with the more common imaging equipment, and introduces constrains as well. The principles of spectral imaging and a few representative applications are described. Spectral imaging analysis is necessary because the complex data structure cannot be analyzed visually. A few of the algorithms are discussed with emphasis on the usage for different experimental modes (fluorescence and bright field). Finally, spectral imaging, like any method, should be evaluated in light of its advantages to specific applications, a selection of which is described. Spectral imaging is a relatively new technique and its full potential is yet to be exploited. Nevertheless, several applications have already shown its potential. (c) 2006 International Society for Analytical Cytology.

[Changes of Forest Canopy Spectral Reflectance with Seasons in Lang Ya Mountains].

PubMed

Li, Wei-tao; Peng, Dao-li; Zhang, Yan; Wu, Jian; Chen, Tai-sheng

2015-08-01

The physiological mechanism and ecological structure of forest trees can change with the changes of years. In a certain extent, the changes were expressed through the canopy spectral features. The mastery of changing rules about spectral characteristics of trees over the years is benefit to remote sensing interpretation and provide scientific basis for the classification of different trees. The study adopted high-resolution spectrometer to measure the canopy spectral characteristics for seven major deciduous trees and seven evergreen trees to gain the spectrum curve of four different ages and calculate the first derivative curve. The analysis of changing rules about spectral characteristics of different deciduous trees and evergreen trees and the comparison of changes about spectrum of various trees in the visible and infrared band could find the best year and best band for identification of trees. The results showed that the canopy spectral reflectance of deciduous and evergreen trees increases with the increase of age. And the spectral changes of two species were most obvious in the near infrared band.

The spectral theorem for quaternionic unbounded normal operators based on the S-spectrum

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alpay, Daniel, E-mail: dany@math.bgu.ac.il; Kimsey, David P., E-mail: dpkimsey@gmail.com; Colombo, Fabrizio, E-mail: fabrizio.colombo@polimi.it

In this paper we prove the spectral theorem for quaternionic unbounded normal operators using the notion of S-spectrum. The proof technique consists of first establishing a spectral theorem for quaternionic bounded normal operators and then using a transformation which maps a quaternionic unbounded normal operator to a quaternionic bounded normal operator. With this paper we complete the foundation of spectral analysis of quaternionic operators. The S-spectrum has been introduced to define the quaternionic functional calculus but it turns out to be the correct object also for the spectral theorem for quaternionic normal operators. The lack of a suitable notion ofmore » spectrum was a major obstruction to fully understand the spectral theorem for quaternionic normal operators. A prime motivation for studying the spectral theorem for quaternionic unbounded normal operators is given by the subclass of unbounded anti-self adjoint quaternionic operators which play a crucial role in the quaternionic quantum mechanics.« less

Spectral reflectance properties (0.4-2.5 um) of secondary Fe-oxide, Fe-hydroxide, and Fe-sulfate-hydrate minerals associated with sulfide-bearing mine waste

USGS Publications Warehouse

Crowley, J.K.; Williams, D.E.; Hammarstrom1, J.M.; Piatak, N.; Mars, J.C.; Chou, I-Ming

2006-01-01

Fifteen Fe-oxide, Fe-hydroxide, and Fe-sulphate-hydrate mineral species commonly associated with sulphide bearing mine wastes were characterized by using X-ray powder diffraction and scanning electron microscope methods. Diffuse reflectance spectra of the samples show diagnostic absorption features related to electronic processes involving ferric and/or ferrous iron, and to vibrational processes involving water and hydroxyl ions. Such spectral features enable field and remote sensing based studies of the mineral distributions. Because secondary minerals are sensitive indicators of pH, Eh, relative humidity, and other environmental conditions, spectral mapping of these minerals promises to have important applications to mine waste remediation studies. This report releases digital (ascii) spectra (spectral_data_files.zip) of the fifteen mineral samples to facilitate usage of the data with spectral libraries and spectral analysis software. The spectral data are provided in a two-column format listing wavelength (in micrometers) and reflectance, respectively.

Physical Interpretation of the Correlation Between Multi-Angle Spectral Data and Canopy Height

NASA Technical Reports Server (NTRS)

Schull, M. A.; Ganguly, S.; Samanta, A.; Huang, D.; Shabanov, N. V.; Jenkins, J. P.; Chiu, J. C.; Marshak, A.; Blair, J. B.; Myneni, R. B.;

[Rapid assessment of critical quality attributes of Chinese materia medica (II): strategy of NIR assignment].

PubMed

Pei, Yan-Ling; Wu, Zhi-Sheng; Shi, Xin-Yuan; Zhou, Lu-Wei; Qiao, Yan-Jiang

2014-09-01

The present paper firstly reviewed the research progress and main methods of NIR spectral assignment coupled with our research results. Principal component analysis was focused on characteristic signal extraction to reflect spectral differences. Partial least squares method was concerned with variable selection to discover characteristic absorption band. Two-dimensional correlation spectroscopy was mainly adopted for spectral assignment. Autocorrelation peaks were obtained from spectral changes, which were disturbed by external factors, such as concentration, temperature and pressure. Density functional theory was used to calculate energy from substance structure to establish the relationship between molecular energy and spectra change. Based on the above reviewed method, taking a NIR spectral assignment of chlorogenic acid as example, a reliable spectral assignment for critical quality attributes of Chinese materia medica (CMM) was established using deuterium technology and spectral variable selection. The result demonstrated the assignment consistency according to spectral features of different concentrations of chlorogenic acid and variable selection region of online NIR model in extract process. Although spectral assignment was initial using an active pharmaceutical ingredient, it is meaningful to look forward to the futurity of the complex components in CMM. Therefore, it provided methodology for NIR spectral assignment of critical quality attributes in CMM.